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KIAC, M. ŘÍHA, K. PŘINOSIL, J. MRNUŠTÍK, J.
Original Title
Object Detection in Unmanned Aerial Vehicle Camera Stream Using Deep Neural Network
Type
conference paper
Language
English
Original Abstract
Nowadays, the world is experiencing an increasing boom in applications of artificial intelligence, especially deep learning. This is more and more used in many areas such as industry, medicine and security systems, etc. This article deals with object detection from Unmanned Aerial Vehicle (UAV) perspective. The whole system uses one camera, which is suitably positioned on the UAV to capture the scene. Image processing and subsequent object detection using the YOLOv4 model are performed on the Jetson Nano device. The device itself is relatively powerful, but to save the computing power of the device, the YOLOv4 neural network model was modified. The YOLOv4 model was trained on our own dataset. This training set was created specifically for UAV applications. The result of this work is a learned YOLOv4 neural network model designed for UAVs with regard to the used training set. The modified network model is also able to run in real-time and save computing power for possibly other UAV operations. All materials, dataset and scripts used in this work, are available at https://github.com/KicoSVK/object-detection-in-uav-using-yolov4.
Keywords
object detection; unmanned aerial vehicle; deep learning; convolutional neural network
Authors
KIAC, M.; ŘÍHA, K.; PŘINOSIL, J.; MRNUŠTÍK, J.
Released
12. 10. 2022
Publisher
IEEE
Location
Valencia, Spain
ISBN
979-8-3503-9866-3
Book
Proceedings of the 2021 13th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)
2157-023X
Periodical
International Congress on Ultra Modern Telecommunications and Control Systems and Workshops
State
unknown
Pages from
80
Pages to
84
Pages count
5
URL
https://ieeexplore.ieee.org/xpl/conhome/1800005/all-proceedings
BibTex
@inproceedings{BUT180026, author="Martin {Kiac} and Kamil {Říha} and Jiří {Přinosil} and Jiří {Mrnuštík}", title="Object Detection in Unmanned Aerial Vehicle Camera Stream Using Deep Neural Network", booktitle="Proceedings of the 2021 13th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)", year="2022", journal="International Congress on Ultra Modern Telecommunications and Control Systems and Workshops", pages="80--84", publisher="IEEE", address="Valencia, Spain", doi="10.1109/ICUMT57764.2022.9943463", isbn="979-8-3503-9866-3", issn="2157-023X", url="https://ieeexplore.ieee.org/xpl/conhome/1800005/all-proceedings" }