TY  - CONF
AU  - Ilić, Jelena
AU  - Medojević, Ivana
AU  - Janković, Novica
PY  - 2023
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/7171
AB  - In the last decades, the field of fluid dynamics has evolved significantly thanks to the
development of experimental and measurement techniques (hot wire, LDA, PTV, PIV), as well as
the increasing computational capabilities and the improvement of available software and
methods, such as CFD. All these techniques generate enormous volumes of data. Extracting
valuable and useful information from them is often a time-consuming task, that could be aided by
Deep Learning (DL). Herein, some of the many possible applications of DL, in particular the
YOLO algorithm, in the practice of PIV, are considered and suggested.
T1  - DEEP LEARNING IN PIV APPLICATIONS
UR  - https://hdl.handle.net/21.15107/rcub_machinery_7171
ER  - 

@conference{
author = "Ilić, Jelena and Medojević, Ivana and Janković, Novica",
year = "2023",
abstract = "In the last decades, the field of fluid dynamics has evolved significantly thanks to the
development of experimental and measurement techniques (hot wire, LDA, PTV, PIV), as well as
the increasing computational capabilities and the improvement of available software and
methods, such as CFD. All these techniques generate enormous volumes of data. Extracting
valuable and useful information from them is often a time-consuming task, that could be aided by
Deep Learning (DL). Herein, some of the many possible applications of DL, in particular the
YOLO algorithm, in the practice of PIV, are considered and suggested.",
title = "DEEP LEARNING IN PIV APPLICATIONS",
url = "https://hdl.handle.net/21.15107/rcub_machinery_7171"
}

Ilić, J., Medojević, I.,& Janković, N.. (2023). DEEP LEARNING IN PIV APPLICATIONS. .
https://hdl.handle.net/21.15107/rcub_machinery_7171

Ilić J, Medojević I, Janković N. DEEP LEARNING IN PIV APPLICATIONS. 2023;.
https://hdl.handle.net/21.15107/rcub_machinery_7171 .

Ilić, Jelena, Medojević, Ivana, Janković, Novica, "DEEP LEARNING IN PIV APPLICATIONS" (2023),
https://hdl.handle.net/21.15107/rcub_machinery_7171 .

TY  - CONF
AU  - Medojević, Ivana
AU  - Ilić, Jelena
PY  - 2023
UR  - https://www.etran.rs/2023/E_ZBORNIK_ETRAN_2023/ETRAN23_RADOVI/SSDI1.2.pdf
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/7177
AB  - In the contemporary food processing industry,
there is a tendency to automatize sorting process along with
minimizing the waist. Therefore, the efforts to improve large –
capacity industrial systems for the sorting of agricultural
products are constant and go from various image processing
techniques towards the area of machine learning. Among deep
learning techniques, You Only Look Once (YOLO) algorithm
offers the potential of recognizing and determining the location
of noncompliant products. In this paper, the study that evaluates
the performance of YOLOv3 algorithm in sorting of raspberries
is represented, together with a logical solution model of a
centralized color sorting system and developed web application.
PB  - Društvo za ETRAN: Akademska misao, Beograd
C3  - Зборник радова LXVII конференције ЕТРАН, Источно Сарајево, 5 ‐ 8. јун 2023.
T1  - The Prospects of YOLO Algorithm Applicaion in the Sorting of Agricultural Products
EP  - SSDI1.2 - 4
SP  - SSDI1.2 - 1
UR  - https://hdl.handle.net/21.15107/rcub_machinery_7177
ER  - 

@conference{
author = "Medojević, Ivana and Ilić, Jelena",
year = "2023",
abstract = "In the contemporary food processing industry,
there is a tendency to automatize sorting process along with
minimizing the waist. Therefore, the efforts to improve large –
capacity industrial systems for the sorting of agricultural
products are constant and go from various image processing
techniques towards the area of machine learning. Among deep
learning techniques, You Only Look Once (YOLO) algorithm
offers the potential of recognizing and determining the location
of noncompliant products. In this paper, the study that evaluates
the performance of YOLOv3 algorithm in sorting of raspberries
is represented, together with a logical solution model of a
centralized color sorting system and developed web application.",
publisher = "Društvo za ETRAN: Akademska misao, Beograd",
journal = "Зборник радова LXVII конференције ЕТРАН, Источно Сарајево, 5 ‐ 8. јун 2023.",
title = "The Prospects of YOLO Algorithm Applicaion in the Sorting of Agricultural Products",
pages = "SSDI1.2 - 4-SSDI1.2 - 1",
url = "https://hdl.handle.net/21.15107/rcub_machinery_7177"
}

Medojević, I.,& Ilić, J.. (2023). The Prospects of YOLO Algorithm Applicaion in the Sorting of Agricultural Products. in Зборник радова LXVII конференције ЕТРАН, Источно Сарајево, 5 ‐ 8. јун 2023.
Društvo za ETRAN: Akademska misao, Beograd., SSDI1.2 - 1-SSDI1.2 - 4.
https://hdl.handle.net/21.15107/rcub_machinery_7177

Medojević I, Ilić J. The Prospects of YOLO Algorithm Applicaion in the Sorting of Agricultural Products. in Зборник радова LXVII конференције ЕТРАН, Источно Сарајево, 5 ‐ 8. јун 2023.. 2023;:SSDI1.2 - 1-SSDI1.2 - 4.
https://hdl.handle.net/21.15107/rcub_machinery_7177 .

Medojević, Ivana, Ilić, Jelena, "The Prospects of YOLO Algorithm Applicaion in the Sorting of Agricultural Products" in Зборник радова LXVII конференције ЕТРАН, Источно Сарајево, 5 ‐ 8. јун 2023. (2023):SSDI1.2 - 1-SSDI1.2 - 4,
https://hdl.handle.net/21.15107/rcub_machinery_7177 .

TY  - JOUR
AU  - Medojević, Ivana
AU  - Veg, Emil
AU  - Joksimović, Aleksandra
AU  - Ilić, Jelena
PY  - 2022
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4477
AB  - Color sorting is a technological operation performed with the aim of classifying compliant and noncompliant agricultural products in large-capacity industrial systems for agricultural product processing. This paper investigates the application of the YOLOv3 algorithm on raspberry images as a method developed for the detection, localization, and classification of objects based on convolutional neural networks (CNNs). To our knowledge, this is the first time a YOLO algorithm or CNN has been used with original images from the color sorter to focus on agricultural products. Results of the F1 measure were in the 92–97% range. Images in full resolution, 1024 × 1024, produced an average detection time of 0.37 s. The impact of the hyperparameters that define the YOLOv3 model as well as the impact of the application of the chosen augmentative methods on the model are evaluated. The successful classification of stalks, which is particularly challenging due to their shape, small dimensions, and variations, was achieved. The presented model demonstrates the ability to classify noncompliant products into four classes, some of which are appropriate for reprocessing. The software, including a graphic interface that enables the real-time testing of machine learning algorithm, is developed and presented.
PB  - MDPI
T2  - Aplied Sciences
T1  - Promotion of Color Sorting in Industrial Systems Using a Deep Learning Algorithm
IS  - 24
SP  - 12817
VL  - 12
DO  - 10.3390/app122412817
ER  - 

@article{
author = "Medojević, Ivana and Veg, Emil and Joksimović, Aleksandra and Ilić, Jelena",
year = "2022",
abstract = "Color sorting is a technological operation performed with the aim of classifying compliant and noncompliant agricultural products in large-capacity industrial systems for agricultural product processing. This paper investigates the application of the YOLOv3 algorithm on raspberry images as a method developed for the detection, localization, and classification of objects based on convolutional neural networks (CNNs). To our knowledge, this is the first time a YOLO algorithm or CNN has been used with original images from the color sorter to focus on agricultural products. Results of the F1 measure were in the 92–97% range. Images in full resolution, 1024 × 1024, produced an average detection time of 0.37 s. The impact of the hyperparameters that define the YOLOv3 model as well as the impact of the application of the chosen augmentative methods on the model are evaluated. The successful classification of stalks, which is particularly challenging due to their shape, small dimensions, and variations, was achieved. The presented model demonstrates the ability to classify noncompliant products into four classes, some of which are appropriate for reprocessing. The software, including a graphic interface that enables the real-time testing of machine learning algorithm, is developed and presented.",
publisher = "MDPI",
journal = "Aplied Sciences",
title = "Promotion of Color Sorting in Industrial Systems Using a Deep Learning Algorithm",
number = "24",
pages = "12817",
volume = "12",
doi = "10.3390/app122412817"
}

Medojević, I., Veg, E., Joksimović, A.,& Ilić, J.. (2022). Promotion of Color Sorting in Industrial Systems Using a Deep Learning Algorithm. in Aplied Sciences
MDPI., 12(24), 12817.
https://doi.org/10.3390/app122412817

Medojević I, Veg E, Joksimović A, Ilić J. Promotion of Color Sorting in Industrial Systems Using a Deep Learning Algorithm. in Aplied Sciences. 2022;12(24):12817.
doi:10.3390/app122412817 .

Medojević, Ivana, Veg, Emil, Joksimović, Aleksandra, Ilić, Jelena, "Promotion of Color Sorting in Industrial Systems Using a Deep Learning Algorithm" in Aplied Sciences, 12, no. 24 (2022):12817,
https://doi.org/10.3390/app122412817 . .

TY  - CONF
AU  - Medojević, Ivana
AU  - Marković, Dragan
AU  - Simonović, Vojislav
AU  - Ilić, Jelena
AU  - Joksimović, Aleksandra
AU  - Veg, Emil
PY  - 2020
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4671
AB  - Machine inspection is a mandatory technological process in industrial processing agriculture products. The camera detects color and shape based irregularities of the object resulting in a large number of parameters for decision-making and sorting product compliance. The goal was to discover a new criterion for decision-making using only the output signal of the RGB camera. Research employed the digital images of raspberries, blackberries, peas and yellow beans during real processing, obtained from a color sorter machine. The visual texture of the surface of the agricultural products was described via defined statistical indicators of color (color average value (Avg), standard deviation (Stdv), entropy (E), and lacunarity (L) was used from the sphere of image fractal analysis as one of the criteria. By applying the non-parametric tests: Wilcoxon signed rank and Friedman test, statistically significant difference was established for the L and Е criteria between compliant and non-compliant industrial products
PB  - SCIENTIFIC-TECHNICAL UNION OF MECHANICAL ENGINEERING “INDUSTRY 4.0"
C3  - Proceedings Industry 4.0. V International Scientific Conference - Winter Session
T1  - Imаge Segmentation Of Agricultural Products Using Statistical Indicators
EP  - 160
SP  - 155
VL  - 2
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4671
ER  - 

@conference{
author = "Medojević, Ivana and Marković, Dragan and Simonović, Vojislav and Ilić, Jelena and Joksimović, Aleksandra and Veg, Emil",
year = "2020",
abstract = "Machine inspection is a mandatory technological process in industrial processing agriculture products. The camera detects color and shape based irregularities of the object resulting in a large number of parameters for decision-making and sorting product compliance. The goal was to discover a new criterion for decision-making using only the output signal of the RGB camera. Research employed the digital images of raspberries, blackberries, peas and yellow beans during real processing, obtained from a color sorter machine. The visual texture of the surface of the agricultural products was described via defined statistical indicators of color (color average value (Avg), standard deviation (Stdv), entropy (E), and lacunarity (L) was used from the sphere of image fractal analysis as one of the criteria. By applying the non-parametric tests: Wilcoxon signed rank and Friedman test, statistically significant difference was established for the L and Е criteria between compliant and non-compliant industrial products",
publisher = "SCIENTIFIC-TECHNICAL UNION OF MECHANICAL ENGINEERING “INDUSTRY 4.0"",
journal = "Proceedings Industry 4.0. V International Scientific Conference - Winter Session",
title = "Imаge Segmentation Of Agricultural Products Using Statistical Indicators",
pages = "160-155",
volume = "2",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4671"
}

Medojević, I., Marković, D., Simonović, V., Ilić, J., Joksimović, A.,& Veg, E.. (2020). Imаge Segmentation Of Agricultural Products Using Statistical Indicators. in Proceedings Industry 4.0. V International Scientific Conference - Winter Session
SCIENTIFIC-TECHNICAL UNION OF MECHANICAL ENGINEERING “INDUSTRY 4.0"., 2, 155-160.
https://hdl.handle.net/21.15107/rcub_machinery_4671

Medojević I, Marković D, Simonović V, Ilić J, Joksimović A, Veg E. Imаge Segmentation Of Agricultural Products Using Statistical Indicators. in Proceedings Industry 4.0. V International Scientific Conference - Winter Session. 2020;2:155-160.
https://hdl.handle.net/21.15107/rcub_machinery_4671 .

Medojević, Ivana, Marković, Dragan, Simonović, Vojislav, Ilić, Jelena, Joksimović, Aleksandra, Veg, Emil, "Imаge Segmentation Of Agricultural Products Using Statistical Indicators" in Proceedings Industry 4.0. V International Scientific Conference - Winter Session, 2 (2020):155-160,
https://hdl.handle.net/21.15107/rcub_machinery_4671 .

TY  - CONF
AU  - Simonović, Vojislav
AU  - Simonović, Andrej
AU  - Marković, Dragan
AU  - Krstić, Dragan
AU  - Medojević, Ivana
AU  - Zlatanović, Ivan
PY  - 2020
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4963
AB  - This paper presents a case study of a barley field experiment that was periodically scouted using a drone spectral camera. The camera has 4 bands so barley was scouted using 4 wavelengths of light - Green, Red, Red Edge and Nir Infra Red (NIR). Based on these wavelengths it is possible to calculate different vegetation indexes known in science and practice. In this paper, 15 such indices were used. The research work concerned the observation of correlation between individual wavelengths and corresponding vegetation indexes. This paper seeks to emphasize the importance of particular wavelengths and spectral areas in crop scouting
PB  - Scientific-Technical Union of Mechanical Engineering
C3  - Agricultureal Machinery 2020, VIII International scientific congress, 24th – 27th June 2020, Varna, Bulgaria
T1  - Correlation Of Light Wavelengths On Spectral Camera And Vegetation Indexes In Barley Crop Scouting
EP  - 12
SP  - 10
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4963
ER  - 

@conference{
author = "Simonović, Vojislav and Simonović, Andrej and Marković, Dragan and Krstić, Dragan and Medojević, Ivana and Zlatanović, Ivan",
year = "2020",
abstract = "This paper presents a case study of a barley field experiment that was periodically scouted using a drone spectral camera. The camera has 4 bands so barley was scouted using 4 wavelengths of light - Green, Red, Red Edge and Nir Infra Red (NIR). Based on these wavelengths it is possible to calculate different vegetation indexes known in science and practice. In this paper, 15 such indices were used. The research work concerned the observation of correlation between individual wavelengths and corresponding vegetation indexes. This paper seeks to emphasize the importance of particular wavelengths and spectral areas in crop scouting",
publisher = "Scientific-Technical Union of Mechanical Engineering",
journal = "Agricultureal Machinery 2020, VIII International scientific congress, 24th – 27th June 2020, Varna, Bulgaria",
title = "Correlation Of Light Wavelengths On Spectral Camera And Vegetation Indexes In Barley Crop Scouting",
pages = "12-10",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4963"
}

Simonović, V., Simonović, A., Marković, D., Krstić, D., Medojević, I.,& Zlatanović, I.. (2020). Correlation Of Light Wavelengths On Spectral Camera And Vegetation Indexes In Barley Crop Scouting. in Agricultureal Machinery 2020, VIII International scientific congress, 24th – 27th June 2020, Varna, Bulgaria
Scientific-Technical Union of Mechanical Engineering., 10-12.
https://hdl.handle.net/21.15107/rcub_machinery_4963

Simonović V, Simonović A, Marković D, Krstić D, Medojević I, Zlatanović I. Correlation Of Light Wavelengths On Spectral Camera And Vegetation Indexes In Barley Crop Scouting. in Agricultureal Machinery 2020, VIII International scientific congress, 24th – 27th June 2020, Varna, Bulgaria. 2020;:10-12.
https://hdl.handle.net/21.15107/rcub_machinery_4963 .

Simonović, Vojislav, Simonović, Andrej, Marković, Dragan, Krstić, Dragan, Medojević, Ivana, Zlatanović, Ivan, "Correlation Of Light Wavelengths On Spectral Camera And Vegetation Indexes In Barley Crop Scouting" in Agricultureal Machinery 2020, VIII International scientific congress, 24th – 27th June 2020, Varna, Bulgaria (2020):10-12,
https://hdl.handle.net/21.15107/rcub_machinery_4963 .

TY  - CONF
AU  - Simonović, Vojislav
AU  - Marković, Dragan
AU  - Medojević, Ivana
AU  - Joksimović, Aleksandra
AU  - Tasić, Nevena
PY  - 2019
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4957
AB  - When preparing a crop scouting mission using UAS, two parameters are set: flight altitude and overlap of images. In practice, crop scouting is most often done at altitudes of 70 to 100 meters, and the switchover is most often between 50 and 100%. The research question that is dealt with in this paper is whether there is a significant difference in the obtained light reflection indexes and consequently postprocessed vegetation indexes, depending on height and overlap. The flight height of the UAS dictates spatial resolution, and the switching dictates the time resolution of the 
reconnaissance. The research was carried out on the experimental plot of barley. The missions were consecutive and performed in perfect weather conditions. The sky was clear, and the light was approximately uniform during all missions with variable heights and overlaps.
PB  - University of Belgrade, Faculty of Agriculture, Department for Agricultural Engineering,  Belgrade, Serbia
C3  - The Fourth International Symposium on  Agricultural Engineering  ISAE-2019
T1  - Flight Altitude Of Uas And Overlap Of Images By Multispectral Camera Optimization For Crop Scouting
EP  - I-49
SP  - I-46
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4957
ER  - 

@conference{
author = "Simonović, Vojislav and Marković, Dragan and Medojević, Ivana and Joksimović, Aleksandra and Tasić, Nevena",
year = "2019",
abstract = "When preparing a crop scouting mission using UAS, two parameters are set: flight altitude and overlap of images. In practice, crop scouting is most often done at altitudes of 70 to 100 meters, and the switchover is most often between 50 and 100%. The research question that is dealt with in this paper is whether there is a significant difference in the obtained light reflection indexes and consequently postprocessed vegetation indexes, depending on height and overlap. The flight height of the UAS dictates spatial resolution, and the switching dictates the time resolution of the 
reconnaissance. The research was carried out on the experimental plot of barley. The missions were consecutive and performed in perfect weather conditions. The sky was clear, and the light was approximately uniform during all missions with variable heights and overlaps.",
publisher = "University of Belgrade, Faculty of Agriculture, Department for Agricultural Engineering,  Belgrade, Serbia",
journal = "The Fourth International Symposium on  Agricultural Engineering  ISAE-2019",
title = "Flight Altitude Of Uas And Overlap Of Images By Multispectral Camera Optimization For Crop Scouting",
pages = "I-49-I-46",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4957"
}

Simonović, V., Marković, D., Medojević, I., Joksimović, A.,& Tasić, N.. (2019). Flight Altitude Of Uas And Overlap Of Images By Multispectral Camera Optimization For Crop Scouting. in The Fourth International Symposium on  Agricultural Engineering  ISAE-2019
University of Belgrade, Faculty of Agriculture, Department for Agricultural Engineering,  Belgrade, Serbia., I-46-I-49.
https://hdl.handle.net/21.15107/rcub_machinery_4957

Simonović V, Marković D, Medojević I, Joksimović A, Tasić N. Flight Altitude Of Uas And Overlap Of Images By Multispectral Camera Optimization For Crop Scouting. in The Fourth International Symposium on  Agricultural Engineering  ISAE-2019. 2019;:I-46-I-49.
https://hdl.handle.net/21.15107/rcub_machinery_4957 .

Simonović, Vojislav, Marković, Dragan, Medojević, Ivana, Joksimović, Aleksandra, Tasić, Nevena, "Flight Altitude Of Uas And Overlap Of Images By Multispectral Camera Optimization For Crop Scouting" in The Fourth International Symposium on  Agricultural Engineering  ISAE-2019 (2019):I-46-I-49,
https://hdl.handle.net/21.15107/rcub_machinery_4957 .

TY  - CONF
AU  - Medojević, Ivana
AU  - Marković, Dragan
AU  - Simonović, Vojislav
AU  - Joksimović, Aleksandra
PY  - 2019
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4961
AB  - The inspection and sorting of agricultural products is a necessary technological operation in the agricultural and food industries. Research in this area shows significant potential in improving the inspection and evaluation of fruits, vegetables, the quality of cereals and other agricultural products, as well as the evaluation of the quality of prepared food products by non-destructive methods. As an integrated system, machine vision has been widely used to test, monitor and control various industrial processes. The increasing and complex performance requirements of 
modern machine vision systems require their further improvement through the development of new, intelligent solutions. Automatic non-destructive recognition of the qualitative characteristics of different types of bio products is a constant challenge for researchers, where the imperative is on product and method which is applicable in industrial conditions. In this regard, there is a large number of works with experimental and numerical data collected for different construction solutions and operating conditions. This paper will analyze the development of machine vision as well as its application in agriculture over the last five years. A special part will be guidelines for the direction of further research in the field of optical recognition of agricultural products.
PB  - University of Belgrade, Faculty of Agriculture, Department for Agricultural Engineering
C3  - The Fourth International Symposium on  Agricultural Engineering  ISAE-2019
T1  - Development And Application Of Machine Vision For Inspection Of Agricultural Products
EP  - I-133
SP  - I-126
VL  - 4
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4961
ER  - 

@conference{
author = "Medojević, Ivana and Marković, Dragan and Simonović, Vojislav and Joksimović, Aleksandra",
year = "2019",
abstract = "The inspection and sorting of agricultural products is a necessary technological operation in the agricultural and food industries. Research in this area shows significant potential in improving the inspection and evaluation of fruits, vegetables, the quality of cereals and other agricultural products, as well as the evaluation of the quality of prepared food products by non-destructive methods. As an integrated system, machine vision has been widely used to test, monitor and control various industrial processes. The increasing and complex performance requirements of 
modern machine vision systems require their further improvement through the development of new, intelligent solutions. Automatic non-destructive recognition of the qualitative characteristics of different types of bio products is a constant challenge for researchers, where the imperative is on product and method which is applicable in industrial conditions. In this regard, there is a large number of works with experimental and numerical data collected for different construction solutions and operating conditions. This paper will analyze the development of machine vision as well as its application in agriculture over the last five years. A special part will be guidelines for the direction of further research in the field of optical recognition of agricultural products.",
publisher = "University of Belgrade, Faculty of Agriculture, Department for Agricultural Engineering",
journal = "The Fourth International Symposium on  Agricultural Engineering  ISAE-2019",
title = "Development And Application Of Machine Vision For Inspection Of Agricultural Products",
pages = "I-133-I-126",
volume = "4",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4961"
}

Medojević, I., Marković, D., Simonović, V.,& Joksimović, A.. (2019). Development And Application Of Machine Vision For Inspection Of Agricultural Products. in The Fourth International Symposium on  Agricultural Engineering  ISAE-2019
University of Belgrade, Faculty of Agriculture, Department for Agricultural Engineering., 4, I-126-I-133.
https://hdl.handle.net/21.15107/rcub_machinery_4961

Medojević I, Marković D, Simonović V, Joksimović A. Development And Application Of Machine Vision For Inspection Of Agricultural Products. in The Fourth International Symposium on  Agricultural Engineering  ISAE-2019. 2019;4:I-126-I-133.
https://hdl.handle.net/21.15107/rcub_machinery_4961 .

Medojević, Ivana, Marković, Dragan, Simonović, Vojislav, Joksimović, Aleksandra, "Development And Application Of Machine Vision For Inspection Of Agricultural Products" in The Fourth International Symposium on  Agricultural Engineering  ISAE-2019, 4 (2019):I-126-I-133,
https://hdl.handle.net/21.15107/rcub_machinery_4961 .

TY  - CONF
AU  - Tasić, Nevena
AU  - Marković, Dragan
AU  - Simonović, Vojislav
AU  - Mladenović, Goran
AU  - Medojević, Ivana
AU  - Joksimović, Aleksandra
PY  - 2019
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4958
AB  - This paper presents different methods for detecting changes in the condition of crops and making a special contribution through the presentation of modeling a tractor platform for crop scouting. This platform was designed in the APS LAB laboratory at the Faculty of Mechanical Engineering in Belgrade intended for the placement of spectrometric sensors. The choice of a suitable method or algorithm for the desired crop scouting is crucial for the success of further analysis of the obtained 
data. Four modes of spectrometry are presented. Beside handheld sensors, there are described methods of data capture via drones and satellites. Most of this paper belongs to the use of sensors in the composition of agricultural machines. This type of scouting is the most effective when it is carried out simultaneously with the distribution of mineral nutrients and crop protection. The tractor platform, on which the sensors are located, can be either a worn type or a connecting type that allows connection to a tractor in three-point in the conventional way. Except for the aforementioned ways, the sensors can be placed on the roof of the tractor or directly on the working machines. 
The process of constructing and modeling the front tractor platform is presented in detail in Solid Works program. Apart from the construction shown, there is a possibility of changing the platform. All foreseen and feasible variants are presented in this paper.
PB  - University of Belgrade, Faculty of Agriculture, Department for Agricultural Engineering
C3  - The Fourth International Symposium on  Agricultural Engineering  ISAE-2019
T1  - Modeling Of Tractor Platform For Crop Scouting
EP  - I-18
SP  - I-10
VL  - 4
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4958
ER  - 

@conference{
author = "Tasić, Nevena and Marković, Dragan and Simonović, Vojislav and Mladenović, Goran and Medojević, Ivana and Joksimović, Aleksandra",
year = "2019",
abstract = "This paper presents different methods for detecting changes in the condition of crops and making a special contribution through the presentation of modeling a tractor platform for crop scouting. This platform was designed in the APS LAB laboratory at the Faculty of Mechanical Engineering in Belgrade intended for the placement of spectrometric sensors. The choice of a suitable method or algorithm for the desired crop scouting is crucial for the success of further analysis of the obtained 
data. Four modes of spectrometry are presented. Beside handheld sensors, there are described methods of data capture via drones and satellites. Most of this paper belongs to the use of sensors in the composition of agricultural machines. This type of scouting is the most effective when it is carried out simultaneously with the distribution of mineral nutrients and crop protection. The tractor platform, on which the sensors are located, can be either a worn type or a connecting type that allows connection to a tractor in three-point in the conventional way. Except for the aforementioned ways, the sensors can be placed on the roof of the tractor or directly on the working machines. 
The process of constructing and modeling the front tractor platform is presented in detail in Solid Works program. Apart from the construction shown, there is a possibility of changing the platform. All foreseen and feasible variants are presented in this paper.",
publisher = "University of Belgrade, Faculty of Agriculture, Department for Agricultural Engineering",
journal = "The Fourth International Symposium on  Agricultural Engineering  ISAE-2019",
title = "Modeling Of Tractor Platform For Crop Scouting",
pages = "I-18-I-10",
volume = "4",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4958"
}

Tasić, N., Marković, D., Simonović, V., Mladenović, G., Medojević, I.,& Joksimović, A.. (2019). Modeling Of Tractor Platform For Crop Scouting. in The Fourth International Symposium on  Agricultural Engineering  ISAE-2019
University of Belgrade, Faculty of Agriculture, Department for Agricultural Engineering., 4, I-10-I-18.
https://hdl.handle.net/21.15107/rcub_machinery_4958

Tasić N, Marković D, Simonović V, Mladenović G, Medojević I, Joksimović A. Modeling Of Tractor Platform For Crop Scouting. in The Fourth International Symposium on  Agricultural Engineering  ISAE-2019. 2019;4:I-10-I-18.
https://hdl.handle.net/21.15107/rcub_machinery_4958 .

Tasić, Nevena, Marković, Dragan, Simonović, Vojislav, Mladenović, Goran, Medojević, Ivana, Joksimović, Aleksandra, "Modeling Of Tractor Platform For Crop Scouting" in The Fourth International Symposium on  Agricultural Engineering  ISAE-2019, 4 (2019):I-10-I-18,
https://hdl.handle.net/21.15107/rcub_machinery_4958 .

TY  - JOUR
AU  - Medojević, Ivana
AU  - Marković, Dragan
AU  - Simonović, Vojislav
AU  - Joksimović, Aleksandra
AU  - Šakota-Rosić, Jovana
PY  - 2019
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/3049
AB  - Obećavajući koncept veštačke inteligencije koji beleži intenzivan razvoj u oblasti digitalne obrade slike je duboko učenje (Deep Learning - DL). Intenzivnije istraživanje u okviru ove oblasti beleži se poslednje dve decenije, a primenu poprima i u poljoprivrednoj industriji. U okviru ovog radu opisana je tehnologija DL koja predstavlja deo mašinskog učenja (Machine Learning - ML), bazirajući se na konvolucijske neuralne mreže (Convolution Neural Networks - CNN). Posebnu primenu zauzima u mašinskoj viziji gde omogućava mašinama da uče iz iskustva, prilagođavaju se novim tehnologijama i obavljaju ljudske zadatke. Ulazni podaci mogu biti iz raznovrsnih izvora: od klasičnih digitalnih snimaka kamere do satelitskih snimaka, kao i snimaka dobijenih pomoću hiperspektralnih, termalnih i infrared kamera. Sve je veća popularnost i upotreba dronova na poljoprivrednim površinama, a samom primenom ovih novih tehnologija dolazi se do ogromnog broja podataka koje je potrebno obraditi u realnom vremenu, stoga se i algoritmi DL sve više upotrebljavaju. U radu su prikazane dosadašnje primene CNN u primarnoj i preciznoj poljoprivredi kao i moguće primene DL u budućnosti.
AB  - A promising concept of artificial intelligence that records intense developments in the field of digital imaging is Deep Learning (DL). More intensive research within this field has been recorded over the past two decades, and has been applied in the agricultural industry as well. This paper will describe the DL technology which represents a part of Machine Learning (ML), based on Convolutional Neural Networks (CNN). It takes a special application in a machine vision where it allows machines to learn from experience, adapt to new technologies, and perform human tasks. Input data can be from a variety of sources: from classic digital camera shots to satellite images, as well as from recordings obtained by means of hyperspectral, thermal and infrared cameras. The increasing popularity and use of trunks in agricultural fields is increasing, and the very application of these new technologies leads to the huge amount of data that needs to be processed in real time, therefore, DL algorithms are increasingly used. The paper will summarize the current and considered possible applications of CNN in primary and precise agriculture in the future.
PB  - Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd
T2  - Poljoprivredna tehnika
T1  - Konvolucijske neuronske mreže - primena u preciznoj poljoprivredi
T1  - The convolutional neural networks: Applications in precision agriculture
EP  - 9
IS  - 1
SP  - 1
VL  - 44
DO  - 10.5937/PoljTeh1901001M
ER  - 

@article{
author = "Medojević, Ivana and Marković, Dragan and Simonović, Vojislav and Joksimović, Aleksandra and Šakota-Rosić, Jovana",
year = "2019",
abstract = "Obećavajući koncept veštačke inteligencije koji beleži intenzivan razvoj u oblasti digitalne obrade slike je duboko učenje (Deep Learning - DL). Intenzivnije istraživanje u okviru ove oblasti beleži se poslednje dve decenije, a primenu poprima i u poljoprivrednoj industriji. U okviru ovog radu opisana je tehnologija DL koja predstavlja deo mašinskog učenja (Machine Learning - ML), bazirajući se na konvolucijske neuralne mreže (Convolution Neural Networks - CNN). Posebnu primenu zauzima u mašinskoj viziji gde omogućava mašinama da uče iz iskustva, prilagođavaju se novim tehnologijama i obavljaju ljudske zadatke. Ulazni podaci mogu biti iz raznovrsnih izvora: od klasičnih digitalnih snimaka kamere do satelitskih snimaka, kao i snimaka dobijenih pomoću hiperspektralnih, termalnih i infrared kamera. Sve je veća popularnost i upotreba dronova na poljoprivrednim površinama, a samom primenom ovih novih tehnologija dolazi se do ogromnog broja podataka koje je potrebno obraditi u realnom vremenu, stoga se i algoritmi DL sve više upotrebljavaju. U radu su prikazane dosadašnje primene CNN u primarnoj i preciznoj poljoprivredi kao i moguće primene DL u budućnosti., A promising concept of artificial intelligence that records intense developments in the field of digital imaging is Deep Learning (DL). More intensive research within this field has been recorded over the past two decades, and has been applied in the agricultural industry as well. This paper will describe the DL technology which represents a part of Machine Learning (ML), based on Convolutional Neural Networks (CNN). It takes a special application in a machine vision where it allows machines to learn from experience, adapt to new technologies, and perform human tasks. Input data can be from a variety of sources: from classic digital camera shots to satellite images, as well as from recordings obtained by means of hyperspectral, thermal and infrared cameras. The increasing popularity and use of trunks in agricultural fields is increasing, and the very application of these new technologies leads to the huge amount of data that needs to be processed in real time, therefore, DL algorithms are increasingly used. The paper will summarize the current and considered possible applications of CNN in primary and precise agriculture in the future.",
publisher = "Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd",
journal = "Poljoprivredna tehnika",
title = "Konvolucijske neuronske mreže - primena u preciznoj poljoprivredi, The convolutional neural networks: Applications in precision agriculture",
pages = "9-1",
number = "1",
volume = "44",
doi = "10.5937/PoljTeh1901001M"
}

Medojević, I., Marković, D., Simonović, V., Joksimović, A.,& Šakota-Rosić, J.. (2019). Konvolucijske neuronske mreže - primena u preciznoj poljoprivredi. in Poljoprivredna tehnika
Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd., 44(1), 1-9.
https://doi.org/10.5937/PoljTeh1901001M

Medojević I, Marković D, Simonović V, Joksimović A, Šakota-Rosić J. Konvolucijske neuronske mreže - primena u preciznoj poljoprivredi. in Poljoprivredna tehnika. 2019;44(1):1-9.
doi:10.5937/PoljTeh1901001M .

Medojević, Ivana, Marković, Dragan, Simonović, Vojislav, Joksimović, Aleksandra, Šakota-Rosić, Jovana, "Konvolucijske neuronske mreže - primena u preciznoj poljoprivredi" in Poljoprivredna tehnika, 44, no. 1 (2019):1-9,
https://doi.org/10.5937/PoljTeh1901001M . .

TY  - JOUR
AU  - Joksimović, Aleksandra
AU  - Marković, Dragan
AU  - Simonović, Vojislav
AU  - Medojević, Ivana
PY  - 2018
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/2752
AB  - U inženjerskom projektovanju, problem prostornog rasporeda ima poseban značaj i predmet je istraživanja dugi niz godina. Tu su prisutne dve grupe problema: problem lokacije i problem raspodele elemenata. U domenu industrije problem lokacije je vezan za određivanje najpovoljnijeg mesta (proizvodnog kompleksa) na makro planu. Kada se analizira problem raspodele elemenata, potrebno je pre svega imati uvid u skup potencijalnih površina koje pojedini elementi mogu da zahtevaju u okviru nekog analiziranog sistema. Kako bi se objasnio značaj prostornog rasporeda i ciljevi njegovog uvođenja, potrebno je opisati postojeće konfiguracije linije odabranog proizvoda, na njima prikazati tok materijala, prostorni raspored i stepen automatizacije. Povećanje stepena automatizacije proizvodnih linija može imati samo prednosti, jer se povećava kvalitet gotovog proizvoda, skraćuje proizvodni ciklus i time povećava proizvodnost.
AB  - In engineering design, the problem of layout has a special significance and has been the object of research for many years. There are two groups of problems: the problem of location and the problem of the distribution of elements. In the domain of industry, the location problem is related to determining the most favorable location (production complex) on the macro plan. When analyzing the problem of the distribution of elements, it is first of all necessary to have an insight into the set of potential surfaces that some elements may require within an analyzed system. In order to explain the importance of the spatial configuration and the objectives of its introduction, it is necessary to describe the existing configuration of the line for the production of nougats, to illustrate the flow of materials, the configuration and the degree of automation. Increasing the degree of automation of production lines can only have advantages because it increases the quality of the finished product, shortens the production cycle and therefore increases productivity.
PB  - Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd
T2  - Poljoprivredna tehnika
T1  - Značaj prostornog rasporeda u proizvodnom procesu
T1  - The importance of layout in a production process
EP  - 18
IS  - 4
SP  - 13
VL  - 43
DO  - 10.5937/PoljTeh1804013J
ER  - 

@article{
author = "Joksimović, Aleksandra and Marković, Dragan and Simonović, Vojislav and Medojević, Ivana",
year = "2018",
abstract = "U inženjerskom projektovanju, problem prostornog rasporeda ima poseban značaj i predmet je istraživanja dugi niz godina. Tu su prisutne dve grupe problema: problem lokacije i problem raspodele elemenata. U domenu industrije problem lokacije je vezan za određivanje najpovoljnijeg mesta (proizvodnog kompleksa) na makro planu. Kada se analizira problem raspodele elemenata, potrebno je pre svega imati uvid u skup potencijalnih površina koje pojedini elementi mogu da zahtevaju u okviru nekog analiziranog sistema. Kako bi se objasnio značaj prostornog rasporeda i ciljevi njegovog uvođenja, potrebno je opisati postojeće konfiguracije linije odabranog proizvoda, na njima prikazati tok materijala, prostorni raspored i stepen automatizacije. Povećanje stepena automatizacije proizvodnih linija može imati samo prednosti, jer se povećava kvalitet gotovog proizvoda, skraćuje proizvodni ciklus i time povećava proizvodnost., In engineering design, the problem of layout has a special significance and has been the object of research for many years. There are two groups of problems: the problem of location and the problem of the distribution of elements. In the domain of industry, the location problem is related to determining the most favorable location (production complex) on the macro plan. When analyzing the problem of the distribution of elements, it is first of all necessary to have an insight into the set of potential surfaces that some elements may require within an analyzed system. In order to explain the importance of the spatial configuration and the objectives of its introduction, it is necessary to describe the existing configuration of the line for the production of nougats, to illustrate the flow of materials, the configuration and the degree of automation. Increasing the degree of automation of production lines can only have advantages because it increases the quality of the finished product, shortens the production cycle and therefore increases productivity.",
publisher = "Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd",
journal = "Poljoprivredna tehnika",
title = "Značaj prostornog rasporeda u proizvodnom procesu, The importance of layout in a production process",
pages = "18-13",
number = "4",
volume = "43",
doi = "10.5937/PoljTeh1804013J"
}

Joksimović, A., Marković, D., Simonović, V.,& Medojević, I.. (2018). Značaj prostornog rasporeda u proizvodnom procesu. in Poljoprivredna tehnika
Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd., 43(4), 13-18.
https://doi.org/10.5937/PoljTeh1804013J

Joksimović A, Marković D, Simonović V, Medojević I. Značaj prostornog rasporeda u proizvodnom procesu. in Poljoprivredna tehnika. 2018;43(4):13-18.
doi:10.5937/PoljTeh1804013J .

Joksimović, Aleksandra, Marković, Dragan, Simonović, Vojislav, Medojević, Ivana, "Značaj prostornog rasporeda u proizvodnom procesu" in Poljoprivredna tehnika, 43, no. 4 (2018):13-18,
https://doi.org/10.5937/PoljTeh1804013J . .

TY  - JOUR
AU  - Marković, Dragan
AU  - Simonović, Vojislav
AU  - Tasić, Nevena
AU  - Medojević, Ivana
AU  - Joksimović, Aleksandra
PY  - 2018
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/2751
AB  - Pri merenju i analizi lokacijski specifičnog prinosa poznatijeg kao monitoring prinosa u okviru šireg ciklusa precizne poljoprivrede meri se oko 30 parametara od interesa za mapiranje prinosa i šire. Najvažniji parametri uz podrazumevana tri parametra koja definišu lokaciju (latituda, longituda i elevacija) su maseni prinos zrna i vlažnost zrna. Uz ove podatke tokom monitoringa prinosa u ovom radu posmatrani su i temperatura zrna, brzina kretanja kombajna i odstupanje preciznosti lociranja (DOP). Jednostavnim statističkim testiranjem korelacije između ovih parametara utvrđen je nivo međusobnog uticaja, između ostalog i stepen uticaja svih navedenih i posmatranih parametara na prinos, kao odgovor na istraživačko pitanje da li na prinos utiče još neki parametar osim lokacije i fizičko-hemijskih osobina zemljišta na toj lokaciji. Utvrđen je različit stepen uticajnosti, ali nije otkriven ni jedan značajan dodatni uticaj na prinos izračunat posredstvom merenja i makon samog merenja. Za monitoring prinosa pri žetvi semenske pšenice na imanju 'Mladost' PKB, Tabla 2, korišćen je kombajn Class Lexion 450 sa nadograđenim sistemom za monitoring AGL Technology proizvođača. Za statističku analizu korišćena je parametarska metoda korelacije u okviru softverskog paketa SPSS Statistics v.21.
AB  - When measuring and analyzing site-specific yield known as the yield monitoring within a wider cycle of precise agriculture, about 30 parameters are measured from inertia for mapping yields. The most important parameters with the default three parameters that define the location (latitude, longitude and elevation) are mass grain yield and grain moisture. In addition to this data during the yield monitoring, the temperature of the grain, speed of the combine and delution of precision (DOP) were also observed in this paper. By simple statistical testing of the correlation between these parameters, the level of mutual influence was determined, among other things, the degree of influence of all mentioned and observed parameters on yield, in response to the research question whether the yield affects another parameter other than the location and physical and chemical properties of the land at that location . A different degree of influence was determined, but no significant additional impact on the yield was calculated by measuring and measuring the measurement itself. For the monitoring of the yield of seed wheat harvesting on the 'Mladost' PKB, Tabla 2, the Class Lexion 450 harvester with an upgraded system for monitoring the AGL Technology manufacturer was used. For the statistical analysis, the parametric method of correlation within the software package SPSS Statistics v.21 was used.
PB  - Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd
T2  - Poljoprivredna tehnika
T1  - Međusobni uticaj različitih parametara pri monitoringu prinosa
T1  - Mutual impact of different parameters in yield monitoring
EP  - 7
IS  - 4
SP  - 1
VL  - 43
DO  - 10.5937/PoljTeh1804001M
ER  - 

@article{
author = "Marković, Dragan and Simonović, Vojislav and Tasić, Nevena and Medojević, Ivana and Joksimović, Aleksandra",
year = "2018",
abstract = "Pri merenju i analizi lokacijski specifičnog prinosa poznatijeg kao monitoring prinosa u okviru šireg ciklusa precizne poljoprivrede meri se oko 30 parametara od interesa za mapiranje prinosa i šire. Najvažniji parametri uz podrazumevana tri parametra koja definišu lokaciju (latituda, longituda i elevacija) su maseni prinos zrna i vlažnost zrna. Uz ove podatke tokom monitoringa prinosa u ovom radu posmatrani su i temperatura zrna, brzina kretanja kombajna i odstupanje preciznosti lociranja (DOP). Jednostavnim statističkim testiranjem korelacije između ovih parametara utvrđen je nivo međusobnog uticaja, između ostalog i stepen uticaja svih navedenih i posmatranih parametara na prinos, kao odgovor na istraživačko pitanje da li na prinos utiče još neki parametar osim lokacije i fizičko-hemijskih osobina zemljišta na toj lokaciji. Utvrđen je različit stepen uticajnosti, ali nije otkriven ni jedan značajan dodatni uticaj na prinos izračunat posredstvom merenja i makon samog merenja. Za monitoring prinosa pri žetvi semenske pšenice na imanju 'Mladost' PKB, Tabla 2, korišćen je kombajn Class Lexion 450 sa nadograđenim sistemom za monitoring AGL Technology proizvođača. Za statističku analizu korišćena je parametarska metoda korelacije u okviru softverskog paketa SPSS Statistics v.21., When measuring and analyzing site-specific yield known as the yield monitoring within a wider cycle of precise agriculture, about 30 parameters are measured from inertia for mapping yields. The most important parameters with the default three parameters that define the location (latitude, longitude and elevation) are mass grain yield and grain moisture. In addition to this data during the yield monitoring, the temperature of the grain, speed of the combine and delution of precision (DOP) were also observed in this paper. By simple statistical testing of the correlation between these parameters, the level of mutual influence was determined, among other things, the degree of influence of all mentioned and observed parameters on yield, in response to the research question whether the yield affects another parameter other than the location and physical and chemical properties of the land at that location . A different degree of influence was determined, but no significant additional impact on the yield was calculated by measuring and measuring the measurement itself. For the monitoring of the yield of seed wheat harvesting on the 'Mladost' PKB, Tabla 2, the Class Lexion 450 harvester with an upgraded system for monitoring the AGL Technology manufacturer was used. For the statistical analysis, the parametric method of correlation within the software package SPSS Statistics v.21 was used.",
publisher = "Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd",
journal = "Poljoprivredna tehnika",
title = "Međusobni uticaj različitih parametara pri monitoringu prinosa, Mutual impact of different parameters in yield monitoring",
pages = "7-1",
number = "4",
volume = "43",
doi = "10.5937/PoljTeh1804001M"
}

Marković, D., Simonović, V., Tasić, N., Medojević, I.,& Joksimović, A.. (2018). Međusobni uticaj različitih parametara pri monitoringu prinosa. in Poljoprivredna tehnika
Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd., 43(4), 1-7.
https://doi.org/10.5937/PoljTeh1804001M

Marković D, Simonović V, Tasić N, Medojević I, Joksimović A. Međusobni uticaj različitih parametara pri monitoringu prinosa. in Poljoprivredna tehnika. 2018;43(4):1-7.
doi:10.5937/PoljTeh1804001M .

Marković, Dragan, Simonović, Vojislav, Tasić, Nevena, Medojević, Ivana, Joksimović, Aleksandra, "Međusobni uticaj različitih parametara pri monitoringu prinosa" in Poljoprivredna tehnika, 43, no. 4 (2018):1-7,
https://doi.org/10.5937/PoljTeh1804001M . .

TY  - CONF
AU  - Medojević, Ivana
AU  - Marković, Dragan
AU  - Simonović, Vojislav
AU  - Joksimović, Aleksandra
PY  - 2018
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4955
AB  - Machine learning is a learning field that gives computers the ability to learn without explicitly programming them. The two main components of machine learning are data and algorithms. Algorithms process data, train (train) parameters, and in this way acquire the ability to make decision-making decisions by adapting new data. Machine learning is widespread in various 
fields both in agriculture and in the food industry, either in terms of fruits, vegetables, finished products, cereals or meat industry. It takes a special application in machine vision, which allows machines to learn from experience, adapt to new technologies and perform human tasks. Mechanical vision provides an alternative as an automated, non-destructive and cost effective technique for achieving demands and expectations in terms of health food safety prescribed by international standards. 
The industry will also have a great role to play, including full digitalization and automation of production, or the networking of smart digital devices with products, machines, tools, robots and people. It is imperative to create "smart factories" where autonomous cyber-physical systems monitor physical processes and make decisions, and the ultimate goal is to increase productivity and efficiency, and therefore competitiveness in the global market. Deep Learning is an encouraging concept of artificial intelligence due to its ability to extract features from images and high precision in the field of digital image processing and thus the agricultural and food industry in the field of quality control.
PB  - Novi Sad : Faculty of Technical Sciences, Department of Industrial Engineering and Management
C3  - Proceedings of TEAM 2018:  9th International Scientific and Expert Conference, 10-12th October 2018, Novi Sad
T1  - Application Of Machine Learning In The Color Sorting Of Agrucultural Products
EP  - 332
SP  - 326
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4955
ER  - 

@conference{
author = "Medojević, Ivana and Marković, Dragan and Simonović, Vojislav and Joksimović, Aleksandra",
year = "2018",
abstract = "Machine learning is a learning field that gives computers the ability to learn without explicitly programming them. The two main components of machine learning are data and algorithms. Algorithms process data, train (train) parameters, and in this way acquire the ability to make decision-making decisions by adapting new data. Machine learning is widespread in various 
fields both in agriculture and in the food industry, either in terms of fruits, vegetables, finished products, cereals or meat industry. It takes a special application in machine vision, which allows machines to learn from experience, adapt to new technologies and perform human tasks. Mechanical vision provides an alternative as an automated, non-destructive and cost effective technique for achieving demands and expectations in terms of health food safety prescribed by international standards. 
The industry will also have a great role to play, including full digitalization and automation of production, or the networking of smart digital devices with products, machines, tools, robots and people. It is imperative to create "smart factories" where autonomous cyber-physical systems monitor physical processes and make decisions, and the ultimate goal is to increase productivity and efficiency, and therefore competitiveness in the global market. Deep Learning is an encouraging concept of artificial intelligence due to its ability to extract features from images and high precision in the field of digital image processing and thus the agricultural and food industry in the field of quality control.",
publisher = "Novi Sad : Faculty of Technical Sciences, Department of Industrial Engineering and Management",
journal = "Proceedings of TEAM 2018:  9th International Scientific and Expert Conference, 10-12th October 2018, Novi Sad",
title = "Application Of Machine Learning In The Color Sorting Of Agrucultural Products",
pages = "332-326",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4955"
}

Medojević, I., Marković, D., Simonović, V.,& Joksimović, A.. (2018). Application Of Machine Learning In The Color Sorting Of Agrucultural Products. in Proceedings of TEAM 2018:  9th International Scientific and Expert Conference, 10-12th October 2018, Novi Sad
Novi Sad : Faculty of Technical Sciences, Department of Industrial Engineering and Management., 326-332.
https://hdl.handle.net/21.15107/rcub_machinery_4955

Medojević I, Marković D, Simonović V, Joksimović A. Application Of Machine Learning In The Color Sorting Of Agrucultural Products. in Proceedings of TEAM 2018:  9th International Scientific and Expert Conference, 10-12th October 2018, Novi Sad. 2018;:326-332.
https://hdl.handle.net/21.15107/rcub_machinery_4955 .

Medojević, Ivana, Marković, Dragan, Simonović, Vojislav, Joksimović, Aleksandra, "Application Of Machine Learning In The Color Sorting Of Agrucultural Products" in Proceedings of TEAM 2018:  9th International Scientific and Expert Conference, 10-12th October 2018, Novi Sad (2018):326-332,
https://hdl.handle.net/21.15107/rcub_machinery_4955 .

TY  - JOUR
AU  - Marković, Ivana
AU  - Marković, Dragan
AU  - Ilić, Jelena
AU  - Simonović, Vojislav
AU  - Veg, Emil
AU  - Šiniković, Goran
AU  - Gubeljak, Nenad
PY  - 2018
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/2899
AB  - Food processing industry is moving forward to a full automation of all processes, especially in technological line segments which represent critical control points of food safety. One of these points is color sorting by using machine vision, where inappropriate products are removed. Most important product appearance attributes are color and texture. During food processing, the product is captured by optical devices, mostly color cameras and lasers. The aim of this paper is to investigate new eligibility criteria for digital image segmentation by using only image from the camera. The goal is to describe the texture of the product, based on chosen mathematical measures, and to allow for recognition and then classification according to the predefined range of values in an appropriate class. Images of frozen raspberry were used. Image analysis of color parameters in RGB color space and statistical tests to examine normality of data were carried out. Thereafter, one-way Anova and correlation analysis was performed. Statistically significant difference was found for the values of two indicators: entropy and new criteria were derived from standard deviation, as well as mean values of pixels for every channel, and marked as L. After determining the range of these criteria, a new algorithm was developed for image segmentation written in Matlab. One of the results of applying this algorithm is that more than 80% of good products were recognized.
PB  - Univ Osijek, Tech Fac, Slavonski Brod
T2  - Tehnički vjesnik
T1  - Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products
EP  - 1745
IS  - 6
SP  - 1739
VL  - 25
DO  - 10.17559/TV-20171129091703
ER  - 

@article{
author = "Marković, Ivana and Marković, Dragan and Ilić, Jelena and Simonović, Vojislav and Veg, Emil and Šiniković, Goran and Gubeljak, Nenad",
year = "2018",
abstract = "Food processing industry is moving forward to a full automation of all processes, especially in technological line segments which represent critical control points of food safety. One of these points is color sorting by using machine vision, where inappropriate products are removed. Most important product appearance attributes are color and texture. During food processing, the product is captured by optical devices, mostly color cameras and lasers. The aim of this paper is to investigate new eligibility criteria for digital image segmentation by using only image from the camera. The goal is to describe the texture of the product, based on chosen mathematical measures, and to allow for recognition and then classification according to the predefined range of values in an appropriate class. Images of frozen raspberry were used. Image analysis of color parameters in RGB color space and statistical tests to examine normality of data were carried out. Thereafter, one-way Anova and correlation analysis was performed. Statistically significant difference was found for the values of two indicators: entropy and new criteria were derived from standard deviation, as well as mean values of pixels for every channel, and marked as L. After determining the range of these criteria, a new algorithm was developed for image segmentation written in Matlab. One of the results of applying this algorithm is that more than 80% of good products were recognized.",
publisher = "Univ Osijek, Tech Fac, Slavonski Brod",
journal = "Tehnički vjesnik",
title = "Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products",
pages = "1745-1739",
number = "6",
volume = "25",
doi = "10.17559/TV-20171129091703"
}

Marković, I., Marković, D., Ilić, J., Simonović, V., Veg, E., Šiniković, G.,& Gubeljak, N.. (2018). Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products. in Tehnički vjesnik
Univ Osijek, Tech Fac, Slavonski Brod., 25(6), 1739-1745.
https://doi.org/10.17559/TV-20171129091703

Marković I, Marković D, Ilić J, Simonović V, Veg E, Šiniković G, Gubeljak N. Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products. in Tehnički vjesnik. 2018;25(6):1739-1745.
doi:10.17559/TV-20171129091703 .

Marković, Ivana, Marković, Dragan, Ilić, Jelena, Simonović, Vojislav, Veg, Emil, Šiniković, Goran, Gubeljak, Nenad, "Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products" in Tehnički vjesnik, 25, no. 6 (2018):1739-1745,
https://doi.org/10.17559/TV-20171129091703 . .

TY  - JOUR
AU  - Simonović, Vojislav
AU  - Marković, Dragan
AU  - Marković, Ivana
AU  - Kirin, Snežana
PY  - 2016
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/2310
AB  - The paper analyzes the impact of sensor readings of dry grain mass yield of wheat, barley and rapeseed on combine speed during harvesting on three plots. The combine was fitted with site-specific yield monitoring sensors. This paper displays detailed tables of statistical procedure carried out for wheat in the analysis of combine speed, whereas final results for barley and rapeseed are itemized. After harvest, the three plots were divided into three groups each according to yield levels: low, medium and high, respectively. On the rapeseed plot, the Kruskal-Wallis H test did not reveal statistically significant difference in combine speed between the plot zones that belong to different yield-level groups, chi(2)(2, N = 2187) = 4,570, p = 0,102. On the basis of mean values for group ranks, the highest combine speed on wheat and barley plots has been found in the medium-yield-level group. Therefore, subsequent analysis of differences was conducted between the groups using Mann-Whitney U test. Combine speed during wheat harvest did not differ significantly in the low- and high-yield-level zones of the plot, Z = -1,213 and N = 3453, p = 0,225, while comparison between speeds within the medium-yield-level group to the other two groups exhibited statistically significant difference, effect size being approx. 0,1. During barley harvest, combine speeds differ statistically significantly when all three groups are compared for low and high impact according to Cohen's criterion based on effect size.
PB  - Strojarski Facultet
T2  - Tehnički vjesnik
T1  - Impact of sensor readings of grain mass yield on combine speed
EP  - 162
IS  - 1
SP  - 157
VL  - 23
DO  - 10.17559/TV-20141019192801
ER  - 

@article{
author = "Simonović, Vojislav and Marković, Dragan and Marković, Ivana and Kirin, Snežana",
year = "2016",
abstract = "The paper analyzes the impact of sensor readings of dry grain mass yield of wheat, barley and rapeseed on combine speed during harvesting on three plots. The combine was fitted with site-specific yield monitoring sensors. This paper displays detailed tables of statistical procedure carried out for wheat in the analysis of combine speed, whereas final results for barley and rapeseed are itemized. After harvest, the three plots were divided into three groups each according to yield levels: low, medium and high, respectively. On the rapeseed plot, the Kruskal-Wallis H test did not reveal statistically significant difference in combine speed between the plot zones that belong to different yield-level groups, chi(2)(2, N = 2187) = 4,570, p = 0,102. On the basis of mean values for group ranks, the highest combine speed on wheat and barley plots has been found in the medium-yield-level group. Therefore, subsequent analysis of differences was conducted between the groups using Mann-Whitney U test. Combine speed during wheat harvest did not differ significantly in the low- and high-yield-level zones of the plot, Z = -1,213 and N = 3453, p = 0,225, while comparison between speeds within the medium-yield-level group to the other two groups exhibited statistically significant difference, effect size being approx. 0,1. During barley harvest, combine speeds differ statistically significantly when all three groups are compared for low and high impact according to Cohen's criterion based on effect size.",
publisher = "Strojarski Facultet",
journal = "Tehnički vjesnik",
title = "Impact of sensor readings of grain mass yield on combine speed",
pages = "162-157",
number = "1",
volume = "23",
doi = "10.17559/TV-20141019192801"
}

Simonović, V., Marković, D., Marković, I.,& Kirin, S.. (2016). Impact of sensor readings of grain mass yield on combine speed. in Tehnički vjesnik
Strojarski Facultet., 23(1), 157-162.
https://doi.org/10.17559/TV-20141019192801

Simonović V, Marković D, Marković I, Kirin S. Impact of sensor readings of grain mass yield on combine speed. in Tehnički vjesnik. 2016;23(1):157-162.
doi:10.17559/TV-20141019192801 .

Simonović, Vojislav, Marković, Dragan, Marković, Ivana, Kirin, Snežana, "Impact of sensor readings of grain mass yield on combine speed" in Tehnički vjesnik, 23, no. 1 (2016):157-162,
https://doi.org/10.17559/TV-20141019192801 . .

TY  - JOUR
AU  - Simonović, Vojislav
AU  - Marković, Dragan
AU  - Marković, Ivana
PY  - 2016
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/2338
AB  - This paper analyzes the differences in mass yield of moist rapeseed grain for six different passes of combine harvester along the plot. The Mann-Whitney U test and Z-statistic are used for analysis needs. For harvest pass 1 and pass 4 the Z-value is only 0,211, whereas the statistical significance level to confirm this finding is 0,8333, therefore there is not statistically significant difference between yield levels in mentioned passes. It is established that there are another three pairs of similar harvest passes, of which two are adjacent, while all other passes exhibit statistical difference with respect to the yield. The approximate value of the effect size r indicator is applied for all passes, where a statistically significant difference turned out to exist between them. The highest difference is noted between pass 2 and pass 3, the effect size r value amounting to 0,464, which can be considered a large effect size according to Cohen's criterion. This paper suggests extending the current routine implementation of yield analysis to an automated post-processing system.
PB  - Univ Osijek, Tech Fac, Slavonski Brod
T2  - Tehnički vjesnik
T1  - Testing of site-specific yield in different harvest passes
EP  - 503
IS  - 2
SP  - 499
VL  - 23
DO  - 10.17559/TV-20140930145702
ER  - 

@article{
author = "Simonović, Vojislav and Marković, Dragan and Marković, Ivana",
year = "2016",
abstract = "This paper analyzes the differences in mass yield of moist rapeseed grain for six different passes of combine harvester along the plot. The Mann-Whitney U test and Z-statistic are used for analysis needs. For harvest pass 1 and pass 4 the Z-value is only 0,211, whereas the statistical significance level to confirm this finding is 0,8333, therefore there is not statistically significant difference between yield levels in mentioned passes. It is established that there are another three pairs of similar harvest passes, of which two are adjacent, while all other passes exhibit statistical difference with respect to the yield. The approximate value of the effect size r indicator is applied for all passes, where a statistically significant difference turned out to exist between them. The highest difference is noted between pass 2 and pass 3, the effect size r value amounting to 0,464, which can be considered a large effect size according to Cohen's criterion. This paper suggests extending the current routine implementation of yield analysis to an automated post-processing system.",
publisher = "Univ Osijek, Tech Fac, Slavonski Brod",
journal = "Tehnički vjesnik",
title = "Testing of site-specific yield in different harvest passes",
pages = "503-499",
number = "2",
volume = "23",
doi = "10.17559/TV-20140930145702"
}

Simonović, V., Marković, D.,& Marković, I.. (2016). Testing of site-specific yield in different harvest passes. in Tehnički vjesnik
Univ Osijek, Tech Fac, Slavonski Brod., 23(2), 499-503.
https://doi.org/10.17559/TV-20140930145702

Simonović V, Marković D, Marković I. Testing of site-specific yield in different harvest passes. in Tehnički vjesnik. 2016;23(2):499-503.
doi:10.17559/TV-20140930145702 .

Simonović, Vojislav, Marković, Dragan, Marković, Ivana, "Testing of site-specific yield in different harvest passes" in Tehnički vjesnik, 23, no. 2 (2016):499-503,
https://doi.org/10.17559/TV-20140930145702 . .

TY  - CONF
AU  - Marković, Ivana
AU  - Ilić, Jelena
AU  - Marković, Dragan
AU  - Simonović, Vojislav
AU  - Dejanović, Sanja
AU  - Golubović, Snežana
PY  - 2015
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4651
AB  - Compared to manual inspection, which is inconsistent and subjective, sorters are able to assure product quality and food safety by more effectively identifying and removing defects and foreign material, while at the same time reducing labor costs and improving operating efficiencies. In this paper we analyzed color of the green beans in the way to find certain parameter which defined good color, acceptable for consumers because homogeneity and appearance have a significant impact on the consumer's decision and to see does and how different lighting effect on the color. The color recorded in the image is not an inherent value of observed object, because it is also influenced by the illumination properties (illuminance, spectral intensity distribution, color rendering index), as well as geometry and surfaces of neighboring objects. The CIE La*b* color space gave good results in a way that it define better the ranges of parameter a*.
PB  - Faculty of Mechanical Engineering, University of Belgrade
C3  - Proceedings of TEAM 2015 7th International Scientific and Expert Conference of the International TEAM Society 14–16th October 2015, Belgrade, Serbia
T1  - A simple digital imaging method for the analysis of the color of food surfaces
EP  - 295
SP  - 292
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4651
ER  - 

@conference{
author = "Marković, Ivana and Ilić, Jelena and Marković, Dragan and Simonović, Vojislav and Dejanović, Sanja and Golubović, Snežana",
year = "2015",
abstract = "Compared to manual inspection, which is inconsistent and subjective, sorters are able to assure product quality and food safety by more effectively identifying and removing defects and foreign material, while at the same time reducing labor costs and improving operating efficiencies. In this paper we analyzed color of the green beans in the way to find certain parameter which defined good color, acceptable for consumers because homogeneity and appearance have a significant impact on the consumer's decision and to see does and how different lighting effect on the color. The color recorded in the image is not an inherent value of observed object, because it is also influenced by the illumination properties (illuminance, spectral intensity distribution, color rendering index), as well as geometry and surfaces of neighboring objects. The CIE La*b* color space gave good results in a way that it define better the ranges of parameter a*.",
publisher = "Faculty of Mechanical Engineering, University of Belgrade",
journal = "Proceedings of TEAM 2015 7th International Scientific and Expert Conference of the International TEAM Society 14–16th October 2015, Belgrade, Serbia",
title = "A simple digital imaging method for the analysis of the color of food surfaces",
pages = "295-292",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4651"
}

Marković, I., Ilić, J., Marković, D., Simonović, V., Dejanović, S.,& Golubović, S.. (2015). A simple digital imaging method for the analysis of the color of food surfaces. in Proceedings of TEAM 2015 7th International Scientific and Expert Conference of the International TEAM Society 14–16th October 2015, Belgrade, Serbia
Faculty of Mechanical Engineering, University of Belgrade., 292-295.
https://hdl.handle.net/21.15107/rcub_machinery_4651

Marković I, Ilić J, Marković D, Simonović V, Dejanović S, Golubović S. A simple digital imaging method for the analysis of the color of food surfaces. in Proceedings of TEAM 2015 7th International Scientific and Expert Conference of the International TEAM Society 14–16th October 2015, Belgrade, Serbia. 2015;:292-295.
https://hdl.handle.net/21.15107/rcub_machinery_4651 .

Marković, Ivana, Ilić, Jelena, Marković, Dragan, Simonović, Vojislav, Dejanović, Sanja, Golubović, Snežana, "A simple digital imaging method for the analysis of the color of food surfaces" in Proceedings of TEAM 2015 7th International Scientific and Expert Conference of the International TEAM Society 14–16th October 2015, Belgrade, Serbia (2015):292-295,
https://hdl.handle.net/21.15107/rcub_machinery_4651 .

TY  - JOUR
AU  - Simonović, Vojislav
AU  - Marković, Dragan
AU  - Mladenović, Nikola
AU  - Marković, Ivana
AU  - Čebela, Žarko
PY  - 2015
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/2062
AB  - U ovom radu analizirana je uticaj prinosa tritikala na brzinu kretanja kombajna tokom žetve. Sistem za merenje lokacijski specifičnog prinosa postavljen je na kombajn širine zahvata 6 metara. Nakon žetve prinos je podeljen u tri grupe, kao mali, srednji i velik prinos, i potom pomoću Kruskal-Volisovog H testa analizirana je brzina za svaku grupu prinosa duž parcele. Ustanovljeno je da se na analiziranoj parceli brzine razlikuju i na osnovu srednjih vrednosti rangova grupa zaključeno je da brzina opada sa smanjenjem prinosa, pa se pristupilo naknadnoj analizi razlike među grupama pomoću Man-Vitnijevog U testa. Brzine kretanja kombajna tokom žetve tritikala na analiziranoj parceli razlikuju se statistički značajno pri poređenju sve tri grupe, i to sa malim i srednjim uticajem prema Koenovom kriterijumu. PR Projekat Ministarstva nauke Republike Srbije, br. TR 35043.
AB  - This paper analyzes the effect of triticale yield on the speed of the combine during harvest. Monitoring system for the site-specific yield is mounted to harvester with 6 meters wide header. After harvest, the yield is divided into three groups, as well as small, medium and large yield, and then using the Kruskal-Wallis H test analyzed the rate of speed for each group along the plot. It was found for analyzed field that the speeds different and based on the average value ranges group concluded that the speed decreases with increasing yield, and access the subsequent analysis of the differences between the groups using the Mann-Whitney U test. The speed of the combine during harvest triticale in the analyzed plot differ significantly when comparing the three groups, and small and medium impact to Cohen's criteria based on effect size.
PB  - Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd
T2  - Poljoprivredna tehnika
T1  - Uticaj masenog prinosa tritikala na brzinu žetve
T1  - Impact of triticale mass yield on harvest speed
EP  - 18
IS  - 1
SP  - 11
VL  - 40
UR  - https://hdl.handle.net/21.15107/rcub_machinery_2062
ER  - 

@article{
author = "Simonović, Vojislav and Marković, Dragan and Mladenović, Nikola and Marković, Ivana and Čebela, Žarko",
year = "2015",
abstract = "U ovom radu analizirana je uticaj prinosa tritikala na brzinu kretanja kombajna tokom žetve. Sistem za merenje lokacijski specifičnog prinosa postavljen je na kombajn širine zahvata 6 metara. Nakon žetve prinos je podeljen u tri grupe, kao mali, srednji i velik prinos, i potom pomoću Kruskal-Volisovog H testa analizirana je brzina za svaku grupu prinosa duž parcele. Ustanovljeno je da se na analiziranoj parceli brzine razlikuju i na osnovu srednjih vrednosti rangova grupa zaključeno je da brzina opada sa smanjenjem prinosa, pa se pristupilo naknadnoj analizi razlike među grupama pomoću Man-Vitnijevog U testa. Brzine kretanja kombajna tokom žetve tritikala na analiziranoj parceli razlikuju se statistički značajno pri poređenju sve tri grupe, i to sa malim i srednjim uticajem prema Koenovom kriterijumu. PR Projekat Ministarstva nauke Republike Srbije, br. TR 35043., This paper analyzes the effect of triticale yield on the speed of the combine during harvest. Monitoring system for the site-specific yield is mounted to harvester with 6 meters wide header. After harvest, the yield is divided into three groups, as well as small, medium and large yield, and then using the Kruskal-Wallis H test analyzed the rate of speed for each group along the plot. It was found for analyzed field that the speeds different and based on the average value ranges group concluded that the speed decreases with increasing yield, and access the subsequent analysis of the differences between the groups using the Mann-Whitney U test. The speed of the combine during harvest triticale in the analyzed plot differ significantly when comparing the three groups, and small and medium impact to Cohen's criteria based on effect size.",
publisher = "Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd",
journal = "Poljoprivredna tehnika",
title = "Uticaj masenog prinosa tritikala na brzinu žetve, Impact of triticale mass yield on harvest speed",
pages = "18-11",
number = "1",
volume = "40",
url = "https://hdl.handle.net/21.15107/rcub_machinery_2062"
}

Simonović, V., Marković, D., Mladenović, N., Marković, I.,& Čebela, Ž.. (2015). Uticaj masenog prinosa tritikala na brzinu žetve. in Poljoprivredna tehnika
Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd., 40(1), 11-18.
https://hdl.handle.net/21.15107/rcub_machinery_2062

Simonović V, Marković D, Mladenović N, Marković I, Čebela Ž. Uticaj masenog prinosa tritikala na brzinu žetve. in Poljoprivredna tehnika. 2015;40(1):11-18.
https://hdl.handle.net/21.15107/rcub_machinery_2062 .

Simonović, Vojislav, Marković, Dragan, Mladenović, Nikola, Marković, Ivana, Čebela, Žarko, "Uticaj masenog prinosa tritikala na brzinu žetve" in Poljoprivredna tehnika, 40, no. 1 (2015):11-18,
https://hdl.handle.net/21.15107/rcub_machinery_2062 .

TY  - CONF
AU  - Marković, Ivana
AU  - Ilić, Jelena
AU  - Marković, Dragan
AU  - Simonović, Vojislav
PY  - 2015
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4650
AB  - The color recorded in the image is not an inherent value of observed object, because it is also influenced by the illumination properties, as well as geometry and surfaces of neighboring objects. Numerous studies have developed and investigated image processing procedures in color sorting machines, where as not many of them have considered the influence of illumination on numerical values related to the colors. In this paper, parameters related to the color of corn have been examined. In each image, the corn has been illuminated by one of four different types of light sources. And different luminous intensities of each type of light source have been applied. The processing of obtained images has been performed in MATLAB, and parameters of images in RGB, CIE L*a*b* and HSV color space have been analyzed. Further descriptive statistics analysis has been performed by IBM SPSS. The variations of parameters with the change of light intensity, showed no statistical significance. The change of the type of the light source has a significant impact on all analyzed features.
C3  - Scientific Proceedings XII International Congress "Machines, Technologies, Materials" 2015
T1  - The influence of illumination parameters on the performances of color sorting machines
EP  - 24
SP  - 20
VL  - 1
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4650
ER  - 

@conference{
author = "Marković, Ivana and Ilić, Jelena and Marković, Dragan and Simonović, Vojislav",
year = "2015",
abstract = "The color recorded in the image is not an inherent value of observed object, because it is also influenced by the illumination properties, as well as geometry and surfaces of neighboring objects. Numerous studies have developed and investigated image processing procedures in color sorting machines, where as not many of them have considered the influence of illumination on numerical values related to the colors. In this paper, parameters related to the color of corn have been examined. In each image, the corn has been illuminated by one of four different types of light sources. And different luminous intensities of each type of light source have been applied. The processing of obtained images has been performed in MATLAB, and parameters of images in RGB, CIE L*a*b* and HSV color space have been analyzed. Further descriptive statistics analysis has been performed by IBM SPSS. The variations of parameters with the change of light intensity, showed no statistical significance. The change of the type of the light source has a significant impact on all analyzed features.",
journal = "Scientific Proceedings XII International Congress "Machines, Technologies, Materials" 2015",
title = "The influence of illumination parameters on the performances of color sorting machines",
pages = "24-20",
volume = "1",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4650"
}

Marković, I., Ilić, J., Marković, D.,& Simonović, V.. (2015). The influence of illumination parameters on the performances of color sorting machines. in Scientific Proceedings XII International Congress "Machines, Technologies, Materials" 2015, 1, 20-24.
https://hdl.handle.net/21.15107/rcub_machinery_4650

Marković I, Ilić J, Marković D, Simonović V. The influence of illumination parameters on the performances of color sorting machines. in Scientific Proceedings XII International Congress "Machines, Technologies, Materials" 2015. 2015;1:20-24.
https://hdl.handle.net/21.15107/rcub_machinery_4650 .

Marković, Ivana, Ilić, Jelena, Marković, Dragan, Simonović, Vojislav, "The influence of illumination parameters on the performances of color sorting machines" in Scientific Proceedings XII International Congress "Machines, Technologies, Materials" 2015, 1 (2015):20-24,
https://hdl.handle.net/21.15107/rcub_machinery_4650 .

TY  - JOUR
AU  - Marković, Dragan
AU  - Mladenović, Nikola
AU  - Simonović, Vojislav
AU  - Marković, Ivana
AU  - Stevanović-Masović, Snežana
PY  - 2014
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/1969
AB  - This paper analyzes theoretically the motion and flow of eight fruit types, along rotating sizing machines. It starts from differential equation of fruit motion on a rotating disk of the sizing machine. A universal method that can generally be applied to determine the flow of all types of rotary sizing machine is developed. Flow analysis comprised sized fruit mass and flow. New empirical coefficients were introduced: extent ratio, feed ratio and distribution ratio. In particular, the influence of the relative speed of fruit on the capacity of sizing machines is researched. The results obtained for the adopted values extend, feed and distribution ratio k(e) = 0,7; k(f) = 1; k(d) = 0,5 coincide approximately with those reported to date for fruit flow rate on sizing machines. It was found that flow rates vary considerably, depending on fruit diameter and mass. Fruit numbers flow ranges from 8949 crops/h for apple to 40.157 crops/h for deep frozen raspberry. Mass flow varies from 229,1 kg/h for cherry to 2054,7 kg/h for apple.
PB  - Strojarski Facultet
T2  - Tehnički vjesnik
T1  - Fruit flow calculation on the rotating sizing machines
EP  - 650
IS  - 3
SP  - 645
VL  - 21
UR  - https://hdl.handle.net/21.15107/rcub_machinery_1969
ER  - 

@article{
author = "Marković, Dragan and Mladenović, Nikola and Simonović, Vojislav and Marković, Ivana and Stevanović-Masović, Snežana",
year = "2014",
abstract = "This paper analyzes theoretically the motion and flow of eight fruit types, along rotating sizing machines. It starts from differential equation of fruit motion on a rotating disk of the sizing machine. A universal method that can generally be applied to determine the flow of all types of rotary sizing machine is developed. Flow analysis comprised sized fruit mass and flow. New empirical coefficients were introduced: extent ratio, feed ratio and distribution ratio. In particular, the influence of the relative speed of fruit on the capacity of sizing machines is researched. The results obtained for the adopted values extend, feed and distribution ratio k(e) = 0,7; k(f) = 1; k(d) = 0,5 coincide approximately with those reported to date for fruit flow rate on sizing machines. It was found that flow rates vary considerably, depending on fruit diameter and mass. Fruit numbers flow ranges from 8949 crops/h for apple to 40.157 crops/h for deep frozen raspberry. Mass flow varies from 229,1 kg/h for cherry to 2054,7 kg/h for apple.",
publisher = "Strojarski Facultet",
journal = "Tehnički vjesnik",
title = "Fruit flow calculation on the rotating sizing machines",
pages = "650-645",
number = "3",
volume = "21",
url = "https://hdl.handle.net/21.15107/rcub_machinery_1969"
}

Marković, D., Mladenović, N., Simonović, V., Marković, I.,& Stevanović-Masović, S.. (2014). Fruit flow calculation on the rotating sizing machines. in Tehnički vjesnik
Strojarski Facultet., 21(3), 645-650.
https://hdl.handle.net/21.15107/rcub_machinery_1969

Marković D, Mladenović N, Simonović V, Marković I, Stevanović-Masović S. Fruit flow calculation on the rotating sizing machines. in Tehnički vjesnik. 2014;21(3):645-650.
https://hdl.handle.net/21.15107/rcub_machinery_1969 .

Marković, Dragan, Mladenović, Nikola, Simonović, Vojislav, Marković, Ivana, Stevanović-Masović, Snežana, "Fruit flow calculation on the rotating sizing machines" in Tehnički vjesnik, 21, no. 3 (2014):645-650,
https://hdl.handle.net/21.15107/rcub_machinery_1969 .

TY  - JOUR
AU  - Marković, Dragan
AU  - Mladenović, Nikola
AU  - Simonović, Vojislav
AU  - Marković, Ivana
PY  - 2014
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/1941
AB  - U ovom radu teoretski je analizirano kretanje i protok osam vrsta voća duž rotacionog kalibratora. Polazi se od diferencijalne jednačine kretanja voća na rotirajućem disku kalibratora. Razvijen je opšti model koji može biti primenjen za određivanje protoka za sve tipove rotacionih kalibratora. Analiza protoka obuhvatila je masu i protok kalibriranog voća. Uvedeni su novi iskustveni koeficijenti: koeficijent procentualnog iskorišćenja obima diska, koeficijent punjenja i koeficijent raspodele plodova. Posebno je istražen uticaj relativne brzine voća na kapacitet kalibratora. Za usvojene vrednosti navedenih koeficijenata ke = 0.7, kf = 1, kd = 0.5 dobijeni su rezultati koji se približno poklapaju sa do sada poznatim protocima voća na kalibratorima. Ustanovljeno je da protoci veoma variraju u zavisnosti od dijametra i mase voća. Količinski protok varira od 8949 plod/h za jabuku do 40157 plod/h za duboko zamrznutu malinu. Maseni protok varira od 229,1 kg/h za višnju do 2054,7 kg/h za jabuku.
AB  - This paper analyzes theoretically the motion and mass quantity of eight fruit types, roundish in shape, along rotating sizing machines. Mathematical model of the motion of fruit on the rotating disc is solved in spherical coordinate system which is tied to the disc. The exact solution is simplified introducing assumptions that are do not significantly affect the accuracy of the solution. Starting from differential equation of fruit motion on a rotating disk of the sizing machine, all forces acting on fruit were determined as well as velocities and time necessary for fruit to reach the disk rim if found in some upper position on the cone. Mass quantity analysis comprised sized fruit mass and weight capacity. New empirical coefficients were introduced: extent ratio, feed ratio and distribution ratio. The results obtained for the adopted values ke = 0.7, kf = 1, kd = 0.5 coincide approximately with those reported to date for fruit mass quantity rate on sizing machines. It was found that mass quantity rates vary considerably, depending on fruit diameter and mass. Fruit numbers mass quantity ranges from 8949 crops/h for apple to 40,157 crops/h for deep frozen raspberry. Mass quantity varies from 229.1 kg/h for cherry to 2054.7 kg/h for apple.
PB  - Univerzitet u Beogradu - Mašinski fakultet, Beograd
T2  - FME Transactions
T1  - Modeliranje kretanja i protoka voća na rotacionim kalibratorima
T1  - Modeling the motion and mass quantity of fruit by rotating sizing machines
EP  - 39
IS  - 1
SP  - 34
VL  - 42
DO  - 10.5937/fmet1401034M
ER  - 

@article{
author = "Marković, Dragan and Mladenović, Nikola and Simonović, Vojislav and Marković, Ivana",
year = "2014",
abstract = "U ovom radu teoretski je analizirano kretanje i protok osam vrsta voća duž rotacionog kalibratora. Polazi se od diferencijalne jednačine kretanja voća na rotirajućem disku kalibratora. Razvijen je opšti model koji može biti primenjen za određivanje protoka za sve tipove rotacionih kalibratora. Analiza protoka obuhvatila je masu i protok kalibriranog voća. Uvedeni su novi iskustveni koeficijenti: koeficijent procentualnog iskorišćenja obima diska, koeficijent punjenja i koeficijent raspodele plodova. Posebno je istražen uticaj relativne brzine voća na kapacitet kalibratora. Za usvojene vrednosti navedenih koeficijenata ke = 0.7, kf = 1, kd = 0.5 dobijeni su rezultati koji se približno poklapaju sa do sada poznatim protocima voća na kalibratorima. Ustanovljeno je da protoci veoma variraju u zavisnosti od dijametra i mase voća. Količinski protok varira od 8949 plod/h za jabuku do 40157 plod/h za duboko zamrznutu malinu. Maseni protok varira od 229,1 kg/h za višnju do 2054,7 kg/h za jabuku., This paper analyzes theoretically the motion and mass quantity of eight fruit types, roundish in shape, along rotating sizing machines. Mathematical model of the motion of fruit on the rotating disc is solved in spherical coordinate system which is tied to the disc. The exact solution is simplified introducing assumptions that are do not significantly affect the accuracy of the solution. Starting from differential equation of fruit motion on a rotating disk of the sizing machine, all forces acting on fruit were determined as well as velocities and time necessary for fruit to reach the disk rim if found in some upper position on the cone. Mass quantity analysis comprised sized fruit mass and weight capacity. New empirical coefficients were introduced: extent ratio, feed ratio and distribution ratio. The results obtained for the adopted values ke = 0.7, kf = 1, kd = 0.5 coincide approximately with those reported to date for fruit mass quantity rate on sizing machines. It was found that mass quantity rates vary considerably, depending on fruit diameter and mass. Fruit numbers mass quantity ranges from 8949 crops/h for apple to 40,157 crops/h for deep frozen raspberry. Mass quantity varies from 229.1 kg/h for cherry to 2054.7 kg/h for apple.",
publisher = "Univerzitet u Beogradu - Mašinski fakultet, Beograd",
journal = "FME Transactions",
title = "Modeliranje kretanja i protoka voća na rotacionim kalibratorima, Modeling the motion and mass quantity of fruit by rotating sizing machines",
pages = "39-34",
number = "1",
volume = "42",
doi = "10.5937/fmet1401034M"
}

Marković, D., Mladenović, N., Simonović, V.,& Marković, I.. (2014). Modeliranje kretanja i protoka voća na rotacionim kalibratorima. in FME Transactions
Univerzitet u Beogradu - Mašinski fakultet, Beograd., 42(1), 34-39.
https://doi.org/10.5937/fmet1401034M

Marković D, Mladenović N, Simonović V, Marković I. Modeliranje kretanja i protoka voća na rotacionim kalibratorima. in FME Transactions. 2014;42(1):34-39.
doi:10.5937/fmet1401034M .

Marković, Dragan, Mladenović, Nikola, Simonović, Vojislav, Marković, Ivana, "Modeliranje kretanja i protoka voća na rotacionim kalibratorima" in FME Transactions, 42, no. 1 (2014):34-39,
https://doi.org/10.5937/fmet1401034M . .

TY  - JOUR
AU  - Marković, Dragan
AU  - Pokrajac, Slobodan
AU  - Simonović, Vojislav
AU  - Marković, Ivana
PY  - 2013
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/1618
AB  - U ovom radu ispitan je stepen ušteda pri primeni najsavremenijih tehničkih sistema za satelitsko navođenje i automatsko upravljanje pri obavljanju poljoprivrednih operacija tokom cele sezone. Uzorno imanje bila je Poljoprivredna korporacija Beograd koja se prostire na oko 21.000 hektara obradive površine. Analiziran je uticaj oblika parcele i pravca kretanja agregata traktor - priključna mašina pri kalkulisanju ušteda usled smanjenja preklopa susednih prohoda. Izvršena je analiza ušteda po kulturama (kukuruz, pšenica, soja, šećerna repa i detelina) i po operacijama za svaku kulturu pojedinačno, prema tehnologiji proizvodnje primenjenoj na uzornom imanju. Detaljno su prikazani podaci samo za pšenicu i ječam. Poređenjem ostvarenih stepena uštede zaključeno je pri kojim operacijama je primena navođenja ekonomski najopravdanija i koliki nivo opremljenosti uređajima za navođenje i upravljanje je potreban. Posebno je analizirana funkcionalna zavisnost ekonomskih ušteda u gorivu i inputima za operacije distribucije mineralnog hraniva i hemijske zaštite biljaka. Tabelarno je data procena stepena svih očekivanih ušteda za operacije koje se odnose na pet analiziranih kultura.
AB  - This paper examined the level of savings in the application of the most modern technical systems for satellite guidance and control over performing agricultural operations throughout the season. The exemplary property was Agricultural Corporation Belgrade (PKB), which covers about 21.000 hectares of arable land. The effects of plot shape and direction of movement of tractor-attachment units in calculating the savings from reduced overlapping of adjacent passes were studied. The analysis was carried out of savings per crop (maize, wheat, soybean, sugar beet and alfalfa) and the operations for each crop separately, based on the manufacturing technology applied to an exemplary property. Detailed data are shown only for wheat and barley. Comparing the achieved level of savings, the application of guidance for the type of the most economically viable operations was found as well as the needed equipment level of guidance devices and management. In particular, the analysis involved the functional dependence of the economic savings in fuel and inputs for the operations such as mineral fertilizers distribution and chemical plant protection. Tabulated are the data estimates for the degree of anticipated savings for operations related to the five analyzed crops.
PB  - Visoka poslovna škola strukovnih studija, Novi Sad
T2  - Škola biznisa
T1  - Ekonomska evaluacija GPS tehnologije u poljoprivredi Srbije
T1  - Economic evaluation of GPS technology in Serbian agriculture
EP  - 11
IS  - 3-4
SP  - 1
DO  - 10.5937/skolbiz1304001M
ER  - 

@article{
author = "Marković, Dragan and Pokrajac, Slobodan and Simonović, Vojislav and Marković, Ivana",
year = "2013",
abstract = "U ovom radu ispitan je stepen ušteda pri primeni najsavremenijih tehničkih sistema za satelitsko navođenje i automatsko upravljanje pri obavljanju poljoprivrednih operacija tokom cele sezone. Uzorno imanje bila je Poljoprivredna korporacija Beograd koja se prostire na oko 21.000 hektara obradive površine. Analiziran je uticaj oblika parcele i pravca kretanja agregata traktor - priključna mašina pri kalkulisanju ušteda usled smanjenja preklopa susednih prohoda. Izvršena je analiza ušteda po kulturama (kukuruz, pšenica, soja, šećerna repa i detelina) i po operacijama za svaku kulturu pojedinačno, prema tehnologiji proizvodnje primenjenoj na uzornom imanju. Detaljno su prikazani podaci samo za pšenicu i ječam. Poređenjem ostvarenih stepena uštede zaključeno je pri kojim operacijama je primena navođenja ekonomski najopravdanija i koliki nivo opremljenosti uređajima za navođenje i upravljanje je potreban. Posebno je analizirana funkcionalna zavisnost ekonomskih ušteda u gorivu i inputima za operacije distribucije mineralnog hraniva i hemijske zaštite biljaka. Tabelarno je data procena stepena svih očekivanih ušteda za operacije koje se odnose na pet analiziranih kultura., This paper examined the level of savings in the application of the most modern technical systems for satellite guidance and control over performing agricultural operations throughout the season. The exemplary property was Agricultural Corporation Belgrade (PKB), which covers about 21.000 hectares of arable land. The effects of plot shape and direction of movement of tractor-attachment units in calculating the savings from reduced overlapping of adjacent passes were studied. The analysis was carried out of savings per crop (maize, wheat, soybean, sugar beet and alfalfa) and the operations for each crop separately, based on the manufacturing technology applied to an exemplary property. Detailed data are shown only for wheat and barley. Comparing the achieved level of savings, the application of guidance for the type of the most economically viable operations was found as well as the needed equipment level of guidance devices and management. In particular, the analysis involved the functional dependence of the economic savings in fuel and inputs for the operations such as mineral fertilizers distribution and chemical plant protection. Tabulated are the data estimates for the degree of anticipated savings for operations related to the five analyzed crops.",
publisher = "Visoka poslovna škola strukovnih studija, Novi Sad",
journal = "Škola biznisa",
title = "Ekonomska evaluacija GPS tehnologije u poljoprivredi Srbije, Economic evaluation of GPS technology in Serbian agriculture",
pages = "11-1",
number = "3-4",
doi = "10.5937/skolbiz1304001M"
}

Marković, D., Pokrajac, S., Simonović, V.,& Marković, I.. (2013). Ekonomska evaluacija GPS tehnologije u poljoprivredi Srbije. in Škola biznisa
Visoka poslovna škola strukovnih studija, Novi Sad.(3-4), 1-11.
https://doi.org/10.5937/skolbiz1304001M

Marković D, Pokrajac S, Simonović V, Marković I. Ekonomska evaluacija GPS tehnologije u poljoprivredi Srbije. in Škola biznisa. 2013;(3-4):1-11.
doi:10.5937/skolbiz1304001M .

Marković, Dragan, Pokrajac, Slobodan, Simonović, Vojislav, Marković, Ivana, "Ekonomska evaluacija GPS tehnologije u poljoprivredi Srbije" in Škola biznisa, no. 3-4 (2013):1-11,
https://doi.org/10.5937/skolbiz1304001M . .

TY  - JOUR
AU  - Dragić, Marko
AU  - Dimić, Nikola
AU  - Marković, Dragan
AU  - Simonović, Vojislav
AU  - Marković, Ivana
PY  - 2013
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/1617
AB  - U ovom radu prikazano je jedno konstruktivno rešenje sigurnosnog rama za voćarske traktore i traktore snage do 65 kW koji se koriste u voćarskoj proizvodnji na nagnutim terenima za mašinsko ubiranje (trešenje) koštičavog voća. Prikazani sigurnosni ram može se montirati na postojeće modele traktora, pre svega domaće proizvodnje. U radu je izvršena analiza naponskih stanja posmatranog sigurnosnog rama u režimu neželjenog slučaja prevrtanja traktora. Uobičajena praksa pri ispitivanju i homologaciji sigurnosnih ramova je da se opterete dvostruko većom silom od težine samog traktora. Analiza sigurnosnog rama vršena je pomoću softverskog paketa SolidWorks korišćenjem metode MKE analize. Ram je opterećen silom od 38,2 kN sa bočne strane i sa gornje strane. Dobijeni rezultati ispitivanja ukazuju na zadovoljavajuću bezbednost.
AB  - This paper describes a design of the protective frame orchard tractors and tractor power up to 65kW for use in fruit production on sloping ground for mechanical harvesting (shaking) of stone fruits. Shown protective frame can be mounted on existing models of tractors, primarily domestic production. This paper presents an analysis of the stress state of the observed protective frame mode unwanted case overturning tractor. A common practice in the examination and approval of protective frames to be loaded twice the force of gravity of the tractor. Analysis of the protective frame was done using the software package SolidWorks gain and methods of FEM analysis. Ram is loaded with a horizontal and vertical force of 38,2 kN on the side and from above. The results obtained show a satisfactory security.
PB  - Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd
T2  - Poljoprivredna tehnika
T1  - MKE analiza sigurnosnog rama voćarskog traktora pri prevrtanju
T1  - FEM analysis of protective frame on orchard tractors in rollover case
EP  - 15
IS  - 4
SP  - 9
VL  - 38
UR  - https://hdl.handle.net/21.15107/rcub_machinery_1617
ER  - 

@article{
author = "Dragić, Marko and Dimić, Nikola and Marković, Dragan and Simonović, Vojislav and Marković, Ivana",
year = "2013",
abstract = "U ovom radu prikazano je jedno konstruktivno rešenje sigurnosnog rama za voćarske traktore i traktore snage do 65 kW koji se koriste u voćarskoj proizvodnji na nagnutim terenima za mašinsko ubiranje (trešenje) koštičavog voća. Prikazani sigurnosni ram može se montirati na postojeće modele traktora, pre svega domaće proizvodnje. U radu je izvršena analiza naponskih stanja posmatranog sigurnosnog rama u režimu neželjenog slučaja prevrtanja traktora. Uobičajena praksa pri ispitivanju i homologaciji sigurnosnih ramova je da se opterete dvostruko većom silom od težine samog traktora. Analiza sigurnosnog rama vršena je pomoću softverskog paketa SolidWorks korišćenjem metode MKE analize. Ram je opterećen silom od 38,2 kN sa bočne strane i sa gornje strane. Dobijeni rezultati ispitivanja ukazuju na zadovoljavajuću bezbednost., This paper describes a design of the protective frame orchard tractors and tractor power up to 65kW for use in fruit production on sloping ground for mechanical harvesting (shaking) of stone fruits. Shown protective frame can be mounted on existing models of tractors, primarily domestic production. This paper presents an analysis of the stress state of the observed protective frame mode unwanted case overturning tractor. A common practice in the examination and approval of protective frames to be loaded twice the force of gravity of the tractor. Analysis of the protective frame was done using the software package SolidWorks gain and methods of FEM analysis. Ram is loaded with a horizontal and vertical force of 38,2 kN on the side and from above. The results obtained show a satisfactory security.",
publisher = "Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd",
journal = "Poljoprivredna tehnika",
title = "MKE analiza sigurnosnog rama voćarskog traktora pri prevrtanju, FEM analysis of protective frame on orchard tractors in rollover case",
pages = "15-9",
number = "4",
volume = "38",
url = "https://hdl.handle.net/21.15107/rcub_machinery_1617"
}

Dragić, M., Dimić, N., Marković, D., Simonović, V.,& Marković, I.. (2013). MKE analiza sigurnosnog rama voćarskog traktora pri prevrtanju. in Poljoprivredna tehnika
Univerzitet u Beogradu - Poljoprivredni fakultet - Institut za poljoprivrednu tehniku, Beograd., 38(4), 9-15.
https://hdl.handle.net/21.15107/rcub_machinery_1617

Dragić M, Dimić N, Marković D, Simonović V, Marković I. MKE analiza sigurnosnog rama voćarskog traktora pri prevrtanju. in Poljoprivredna tehnika. 2013;38(4):9-15.
https://hdl.handle.net/21.15107/rcub_machinery_1617 .

Dragić, Marko, Dimić, Nikola, Marković, Dragan, Simonović, Vojislav, Marković, Ivana, "MKE analiza sigurnosnog rama voćarskog traktora pri prevrtanju" in Poljoprivredna tehnika, 38, no. 4 (2013):9-15,
https://hdl.handle.net/21.15107/rcub_machinery_1617 .

TY  - CONF
AU  - Marković, Ivana
AU  - Ilić, Jelena
AU  - Marković, Dragan
AU  - Simonović, Vojislav
AU  - Krstić, Dragan
AU  - Šakota, Jovana
PY  - 2013
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4645
AB  - This paper presents the significant elements of a computer vision system and emphasises the important aspects of the image processing technique coupled with a review of the most recent developments throughout the food industry. Recently automatic inspection systems, mainly based on camera-computer technology have been investigated for the sensory analysis of agricultural and food products. This system known as computer vision has proven to be successful for objective measurement of various agricultural and food products. Computer vision is the construction of explicit and meaningful descriptions of physical objects from images. This review presents the recent developments and applications of image analysis in the food industry, the basic concepts and technologies associated with computer vision.
PB  - Vrnjačka Banja : SaTCIP (Scientific and Technical Center for Intellectual Property) Ltd.
C3  - Proceedings of the 13th International conference “Research and development in mechanical industry” RaDMI 2013
T1  - Using different color spaces in mechanical inspection of fruits and vegetables
EP  - 704
SP  - 700
VL  - 1
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4645
ER  - 

@conference{
author = "Marković, Ivana and Ilić, Jelena and Marković, Dragan and Simonović, Vojislav and Krstić, Dragan and Šakota, Jovana",
year = "2013",
abstract = "This paper presents the significant elements of a computer vision system and emphasises the important aspects of the image processing technique coupled with a review of the most recent developments throughout the food industry. Recently automatic inspection systems, mainly based on camera-computer technology have been investigated for the sensory analysis of agricultural and food products. This system known as computer vision has proven to be successful for objective measurement of various agricultural and food products. Computer vision is the construction of explicit and meaningful descriptions of physical objects from images. This review presents the recent developments and applications of image analysis in the food industry, the basic concepts and technologies associated with computer vision.",
publisher = "Vrnjačka Banja : SaTCIP (Scientific and Technical Center for Intellectual Property) Ltd.",
journal = "Proceedings of the 13th International conference “Research and development in mechanical industry” RaDMI 2013",
title = "Using different color spaces in mechanical inspection of fruits and vegetables",
pages = "704-700",
volume = "1",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4645"
}

Marković, I., Ilić, J., Marković, D., Simonović, V., Krstić, D.,& Šakota, J.. (2013). Using different color spaces in mechanical inspection of fruits and vegetables. in Proceedings of the 13th International conference “Research and development in mechanical industry” RaDMI 2013
Vrnjačka Banja : SaTCIP (Scientific and Technical Center for Intellectual Property) Ltd.., 1, 700-704.
https://hdl.handle.net/21.15107/rcub_machinery_4645

Marković I, Ilić J, Marković D, Simonović V, Krstić D, Šakota J. Using different color spaces in mechanical inspection of fruits and vegetables. in Proceedings of the 13th International conference “Research and development in mechanical industry” RaDMI 2013. 2013;1:700-704.
https://hdl.handle.net/21.15107/rcub_machinery_4645 .

Marković, Ivana, Ilić, Jelena, Marković, Dragan, Simonović, Vojislav, Krstić, Dragan, Šakota, Jovana, "Using different color spaces in mechanical inspection of fruits and vegetables" in Proceedings of the 13th International conference “Research and development in mechanical industry” RaDMI 2013, 1 (2013):700-704,
https://hdl.handle.net/21.15107/rcub_machinery_4645 .

TY  - JOUR
AU  - Marković, Ivana
AU  - Ilić, Jelena
AU  - Marković, Dragan
AU  - Simonović, Vojislav
AU  - Kosanić, Nenad
PY  - 2013
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4647
AB  - Color of the food is the first parameter of quality evaluated by consumers. What is important is the acceptance of the product even before being consumed. Inspection of food products is done using machine vision, particularly analyzing and processing the images, where the parameters of each pixel on the surface of the recorded product must be known. Using different color spaces quantitative color value is obtained. Although there are many different color spaces, when it comes to food, the most frequently used is the CIE L*a*b* color space, due to its uniform color distribution and because its perception of color is closest to the one human eye. RGB color space, where a sensor in each pixel records the intensity of light in the red, green and blue spectrum, is also similar to human perception of colors and it is also frequently used. The problem with the L * a * b * scale is that commercial color-meters measure only a dozen of square centimetres of the product itself and the measurements are not representative for the most of heterogeneous materials. The aim of this paper is to present the analysis of images of chosen food products using the two color spaces. In each of the two color spaces, after determining the range of parameters appropriate to good quality products, the criteria for the discrimination of damaged products is defined and tested. The comparison of the applications of those criteria shows that, in the case of food, the transformation of RGB coordinates into the CIE L*a*b* color space makes it possible to achieve greater accuracy and improved calculation of appropriate color parameters.
PB  - Consulting and Training Center KEY
T2  - Journal of Hygienic Engineering and Design
T1  - Color measurement of food products using CIE l*a*b* and RGB color space
EP  - 53
SP  - 50
VL  - 4
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4647
ER  - 

@article{
author = "Marković, Ivana and Ilić, Jelena and Marković, Dragan and Simonović, Vojislav and Kosanić, Nenad",
year = "2013",
abstract = "Color of the food is the first parameter of quality evaluated by consumers. What is important is the acceptance of the product even before being consumed. Inspection of food products is done using machine vision, particularly analyzing and processing the images, where the parameters of each pixel on the surface of the recorded product must be known. Using different color spaces quantitative color value is obtained. Although there are many different color spaces, when it comes to food, the most frequently used is the CIE L*a*b* color space, due to its uniform color distribution and because its perception of color is closest to the one human eye. RGB color space, where a sensor in each pixel records the intensity of light in the red, green and blue spectrum, is also similar to human perception of colors and it is also frequently used. The problem with the L * a * b * scale is that commercial color-meters measure only a dozen of square centimetres of the product itself and the measurements are not representative for the most of heterogeneous materials. The aim of this paper is to present the analysis of images of chosen food products using the two color spaces. In each of the two color spaces, after determining the range of parameters appropriate to good quality products, the criteria for the discrimination of damaged products is defined and tested. The comparison of the applications of those criteria shows that, in the case of food, the transformation of RGB coordinates into the CIE L*a*b* color space makes it possible to achieve greater accuracy and improved calculation of appropriate color parameters.",
publisher = "Consulting and Training Center KEY",
journal = "Journal of Hygienic Engineering and Design",
title = "Color measurement of food products using CIE l*a*b* and RGB color space",
pages = "53-50",
volume = "4",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4647"
}

Marković, I., Ilić, J., Marković, D., Simonović, V.,& Kosanić, N.. (2013). Color measurement of food products using CIE l*a*b* and RGB color space. in Journal of Hygienic Engineering and Design
Consulting and Training Center KEY., 4, 50-53.
https://hdl.handle.net/21.15107/rcub_machinery_4647

Marković I, Ilić J, Marković D, Simonović V, Kosanić N. Color measurement of food products using CIE l*a*b* and RGB color space. in Journal of Hygienic Engineering and Design. 2013;4:50-53.
https://hdl.handle.net/21.15107/rcub_machinery_4647 .

Marković, Ivana, Ilić, Jelena, Marković, Dragan, Simonović, Vojislav, Kosanić, Nenad, "Color measurement of food products using CIE l*a*b* and RGB color space" in Journal of Hygienic Engineering and Design, 4 (2013):50-53,
https://hdl.handle.net/21.15107/rcub_machinery_4647 .

TY  - CONF
AU  - Marković, Dragan
AU  - Simonović, Vojislav
AU  - Marković, Ivana
AU  - Krstić, Dragan
PY  - 2012
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/1376
AB  - Vegetable production is one of the most intensive industry crop production, indicated by the size of the yield per unit area, earned income, net income and the share of human labor. To achieve high yield and get a quality product, the most important operations in the primary production of vegetables, after preparing the soil, is seeding. This paper presents the technical indicators of sowing devices that significantly affects the quality of sowing. Great progress made to improve the operation and functionality of existing planting equipment and seeder themselves related to the calibration of seeds that must be achieved by applying prescribed legal and appropriate standards.
PB  - Univ Novi Sad, Fac Tech Sci, Adeko, Novi Sad
C3  - Machine and Industrial Design in Mechanical Engineering, Seventh International Symposium, Kod 2012
T1  - State and potentials of use mechanization in vegetable production in Serbia
EP  - 242
SP  - 239
UR  - https://hdl.handle.net/21.15107/rcub_machinery_1376
ER  - 

@conference{
author = "Marković, Dragan and Simonović, Vojislav and Marković, Ivana and Krstić, Dragan",
year = "2012",
abstract = "Vegetable production is one of the most intensive industry crop production, indicated by the size of the yield per unit area, earned income, net income and the share of human labor. To achieve high yield and get a quality product, the most important operations in the primary production of vegetables, after preparing the soil, is seeding. This paper presents the technical indicators of sowing devices that significantly affects the quality of sowing. Great progress made to improve the operation and functionality of existing planting equipment and seeder themselves related to the calibration of seeds that must be achieved by applying prescribed legal and appropriate standards.",
publisher = "Univ Novi Sad, Fac Tech Sci, Adeko, Novi Sad",
journal = "Machine and Industrial Design in Mechanical Engineering, Seventh International Symposium, Kod 2012",
title = "State and potentials of use mechanization in vegetable production in Serbia",
pages = "242-239",
url = "https://hdl.handle.net/21.15107/rcub_machinery_1376"
}

Marković, D., Simonović, V., Marković, I.,& Krstić, D.. (2012). State and potentials of use mechanization in vegetable production in Serbia. in Machine and Industrial Design in Mechanical Engineering, Seventh International Symposium, Kod 2012
Univ Novi Sad, Fac Tech Sci, Adeko, Novi Sad., 239-242.
https://hdl.handle.net/21.15107/rcub_machinery_1376

Marković D, Simonović V, Marković I, Krstić D. State and potentials of use mechanization in vegetable production in Serbia. in Machine and Industrial Design in Mechanical Engineering, Seventh International Symposium, Kod 2012. 2012;:239-242.
https://hdl.handle.net/21.15107/rcub_machinery_1376 .

Marković, Dragan, Simonović, Vojislav, Marković, Ivana, Krstić, Dragan, "State and potentials of use mechanization in vegetable production in Serbia" in Machine and Industrial Design in Mechanical Engineering, Seventh International Symposium, Kod 2012 (2012):239-242,
https://hdl.handle.net/21.15107/rcub_machinery_1376 .