Anti-Drone System: A Visual-based Drone Detection using Neural Networks

초록

A system that secures an area from trespassing drones that might bring threat is in demand these days since drones became easily-available to the public and it became easier to operate. This paper proposes an anti-drone system that uses visual sensing to detect drones. A Faster R-CNN (Region-based Convolutional Neural Network) with ResNet-101 (Residual Neural Network-101) networks are used in this paper using a dataset from the SafeShore project. The network's accuracy is 93.40% and it has successfully detected drones in the simulation that has been done.

제목
Anti-Drone System: A Visual-based Drone Detection using Neural Networks
저자
Garcia, Ann Janeth; Lee, Jae Min; Kim, Dong Seong
DOI
10.1109/ICTC49870.2020.9289397
발행일
2020-10
학회명
11th International Conference on Information and Communication Technology Convergence (ICTC) - Data, Network, and AI in the age of Untact (ICTC)
개최지
Jeju, SOUTH KOREA
개최국가
미국
학회 개최일
2020-10-21 ~ 2020-10-23