Application of YOLO algorithm on student UAV (CROSBI ID 719628)
Prilog sa skupa u zborniku | sažetak izlaganja sa skupa | međunarodna recenzija
Podaci o odgovornosti
Grebo, Alen ; Konsa, Toni ; Gasparovic, Goran ; Klarin, Branko
engleski
Application of YOLO algorithm on student UAV
The main concern of this paper will be to explain the workflow of YOLO2 and YOLO3 object detection algorithms with regards to training on custom dataset for the purpose of deploying said algorithms on NVIDIA Jetson mini board that is placed inside the shell of an unmanned aerial vehicle made for a purpose of student unmanned aerial vehicle(SUAV) competition. A walk through the key concepts and intuition regarding neural nets, typical data augmentation processes, the training process and deployment, both from software and hardware point of view, will be given.
YOLO , YOLOv2 , YOLOv3 , MATLAB , Python , Object detection application , UAV
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Podaci o prilogu
20133283
2020.
objavljeno
10.23919/splitech49282.2020.9243691
Podaci o matičnoj publikaciji
5th International Conference on Smart and Sustainable Technologies (SpliTech 2020)
Šolić, Petar ; Sandro, Nižetić ; Rodrigues, Joel J. P. C. ; López-de-Ipiña González-de-Artaza, Diego ; Perković, Toni ; Catarinucci, Luca ; Patrono, Luigi
Piscataway (NJ): Institute of Electrical and Electronics Engineers (IEEE)
978-953-290-105-4
Podaci o skupu
5th International Conference on Smart and Sustainable Technologies (SpliTech 2020)
predavanje
23.09.2020-26.09.2020
online
Povezanost rada
Interdisciplinarne tehničke znanosti, Računarstvo, Strojarstvo, Zrakoplovstvo, raketna i svemirska tehnika