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Conference Paper The Analysis of UAV Detection Performance Using Rotating Cameras
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Authors
Young-il Kim, Yeo Geon Min, Park Seong Hee, Jeong Wun-Cheol, Song Soonyong, Heo Tae-Wook
Issue Date
2021-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2021, pp.1262-1265
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC52510.2021.9621076
Abstract
With the development of the drone industry, various technologies to detect the increasing illegal intrusion drones are being developed to reduce the damage caused by illegal intrusion drones. Deep learning-based image sensing techniques are useful for detecting and classifying drones at close range, but this requires the use of a large number of cameras. To solve this problem, this paper intends to analyze the detection performance of the unmanned aerial vehicle using the image sensing technology that rotates the camera. To this end, a method of constructing a UAV protection area and a method of rotating the camera in a spiral to increase the opportunity of UAV detection are proposed, and performance analysis based on rotating camera is performed.
KSP Keywords
Close range, Image sensing, Learning-based, Performance analysis, Sensing Technology, UAV detection, deep learning(DL), detection performance, unmanned aerial vehicle(UAV)