Please use this identifier to cite or link to this item: https://doi.org/10.23919/ICCAS52745.2021.9650015
Title: Fast Drone Detection using SSD and YoloV3
Authors: Hao, YJ
Teck, LK
Xiang, CY
Jeevanraj, E
Srigrarom, S 
Issue Date: 1-Jan-2021
Publisher: IEEE
Citation: Hao, YJ, Teck, LK, Xiang, CY, Jeevanraj, E, Srigrarom, S (2021-01-01). Fast Drone Detection using SSD and YoloV3. 2021 21st International Conference on Control, Automation and Systems (ICCAS) 2021-October : 1172-1179. ScholarBank@NUS Repository. https://doi.org/10.23919/ICCAS52745.2021.9650015
Abstract: This paper aims to introduce the method of detection of high-speed drones using both Single Shot Detector (SSD) and YOLOv3 (You Only Look Once)v3. After conducting experiments and obtaining footage of the fast-flying drones, the software and algorithms are being put to the test. In a motion detector, there are 3 main fundamentals-unmanned aerial vehicle (UAV) detection, UAV identification and tracking of the UAV, which will be introduced as a preliminary UAV detection system to spark of the use of other more advanced image recognition based detector. The alternative of using SSD and YOLOv3 will be the main discussion to target high-speed drones.
Source Title: 2021 21st International Conference on Control, Automation and Systems (ICCAS)
URI: https://scholarbank.nus.edu.sg/handle/10635/217737
ISBN: 9788993215212
ISSN: 15987833
DOI: 10.23919/ICCAS52745.2021.9650015
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