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Anti-Drone System: A Visual-based Drone Detection using Neural Networks
- Garcia, Ann Janeth;
- Lee, Jae Min;
- Kim, Dong Seong
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
- 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
- 언어
- ENG