Overview of the use of convolutional neural networks in plant desease recognition based on the leaf image
Апстракт
The use of artificial intelligence in modern agriculture is on the rise, due to the fact that it provides a possibility for more efficient production, better decision making and reduction of the costs. This research takes into consideration the use of the convolutional neural networks for diagnosing plant illnesses based on the leaf image. Detection of plant diseases in the early phase can improve the quality of the food products and minimize the loses. Convolutional neural networks are a type of deep learning method that is one of the most used models for solving image recognition, classification and detection tasks. Therefore, it is justified to anticipate that they can be very effectively applied in the agriculture sector. This paper covers plant species that are the most significant for Serbian production. Various models have been presented and analyzed, while highlighting their advantages and disadvantages when applied for solving this task.
Кључне речи:
Convolutional neural networks / plant disease recognition / artificial intelligenceИзвор:
ISAE 2023, 2023, 13-22Финансирање / пројекти:
- Иновативни приступ у примени интелигентних технолошких система за производњу делова од лима заснован на еколошким принципима (RS-MESTD-Technological Development (TD or TR)-35004)
- Истраживање и развој опреме и система за индустријску производњу, складиштење и прераду поврћа и воћа (RS-MESTD-Technological Development (TD or TR)-35043)
Колекције
Институција/група
Mašinski fakultetTY - CONF AU - Perišić, Natalija AU - Jovanović, Radiša AU - Vesović, Mitra AU - Sretenović, Aleksandra PY - 2023 UR - https://machinery.mas.bg.ac.rs/handle/123456789/7298 AB - The use of artificial intelligence in modern agriculture is on the rise, due to the fact that it provides a possibility for more efficient production, better decision making and reduction of the costs. This research takes into consideration the use of the convolutional neural networks for diagnosing plant illnesses based on the leaf image. Detection of plant diseases in the early phase can improve the quality of the food products and minimize the loses. Convolutional neural networks are a type of deep learning method that is one of the most used models for solving image recognition, classification and detection tasks. Therefore, it is justified to anticipate that they can be very effectively applied in the agriculture sector. This paper covers plant species that are the most significant for Serbian production. Various models have been presented and analyzed, while highlighting their advantages and disadvantages when applied for solving this task. C3 - ISAE 2023 T1 - Overview of the use of convolutional neural networks in plant desease recognition based on the leaf image EP - 22 SP - 13 UR - https://hdl.handle.net/21.15107/rcub_machinery_7298 ER -
@conference{ author = "Perišić, Natalija and Jovanović, Radiša and Vesović, Mitra and Sretenović, Aleksandra", year = "2023", abstract = "The use of artificial intelligence in modern agriculture is on the rise, due to the fact that it provides a possibility for more efficient production, better decision making and reduction of the costs. This research takes into consideration the use of the convolutional neural networks for diagnosing plant illnesses based on the leaf image. Detection of plant diseases in the early phase can improve the quality of the food products and minimize the loses. Convolutional neural networks are a type of deep learning method that is one of the most used models for solving image recognition, classification and detection tasks. Therefore, it is justified to anticipate that they can be very effectively applied in the agriculture sector. This paper covers plant species that are the most significant for Serbian production. Various models have been presented and analyzed, while highlighting their advantages and disadvantages when applied for solving this task.", journal = "ISAE 2023", title = "Overview of the use of convolutional neural networks in plant desease recognition based on the leaf image", pages = "22-13", url = "https://hdl.handle.net/21.15107/rcub_machinery_7298" }
Perišić, N., Jovanović, R., Vesović, M.,& Sretenović, A.. (2023). Overview of the use of convolutional neural networks in plant desease recognition based on the leaf image. in ISAE 2023, 13-22. https://hdl.handle.net/21.15107/rcub_machinery_7298
Perišić N, Jovanović R, Vesović M, Sretenović A. Overview of the use of convolutional neural networks in plant desease recognition based on the leaf image. in ISAE 2023. 2023;:13-22. https://hdl.handle.net/21.15107/rcub_machinery_7298 .
Perišić, Natalija, Jovanović, Radiša, Vesović, Mitra, Sretenović, Aleksandra, "Overview of the use of convolutional neural networks in plant desease recognition based on the leaf image" in ISAE 2023 (2023):13-22, https://hdl.handle.net/21.15107/rcub_machinery_7298 .