DEEP LEARNING IN PIV APPLICATIONS
Само за регистроване кориснике
2023
Конференцијски прилог (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
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.
Кључне речи:
PIV / Deep Learning / YOLO algorithmИзвор:
2023Финансирање / пројекти:
- MNTR 451-03-68/2022-14/200105, "Primena savremenih mernih i proračunskih tehnika za izučavanje strujnih parametara ventilacionih sistema na modelu energetski izuzetno efikasnog (pasivnog) objekta" (RS-35046)
Колекције
Институција/група
Mašinski fakultetTY - 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 .