Infrared target detecting in severe jamming using detector based on Deep Learning
- Resource Type
- Conference
- Authors
- Hu, Yangguang; Xiao, Mingqing; Liu, Zhaozheng; Meng, Jiaojiao; Kuang, Mingjian
- Source
- 2019 IEEE International Conference on Unmanned Systems and Artificial Intelligence (ICUSAI) Unmanned Systems and Artificial Intelligence (ICUSAI), 2019 International Conference on. :71-74 Nov, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Signal Processing and Analysis
Aerial target
Target detecting
IR jamming
Deep Learning
- Language
In recent years, detection algorithms based on deep learning have made great progress. It also provided a new solution to solve the issue to detecting the target in severe jamming. In this paper, the application of deep detectors in infrared target detecting was explored. Experimental results show that YOLOv3 outperformed Faster R-CNN in the aerial target tracking based on infrared images. The target detection algorithm in the field of artificial intelligence has good applicability in the field of infrared target detection.