Deep-Learning Based Algorithm for Detecting Targets in Infrared Images
Source abstract
Abstract
Infrared image target detection technology has been one of the essential research topics in computer vision, which has promoted the development of automatic driving, infrared guidance, infrared surveillance, and other fields. However, traditional target detection algorithms for infrared images have difficulty adapting to the target’s multiscale characteristics. In addition, the accuracy of the detection algorithm is significantly reduced when the target is occluded. The corresponding solutions are proposed in this paper to solve these two problems. The final experiments show that this paper’s infrared image target detection model improves significantly.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Infrared Target Detection Methodologies · Advanced Neural Network Applications · Video Surveillance and Tracking Methods
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Optical and Communication Engineering, Yunnan Open University, Kunming 650000, China
School of Information Technology and Management, Hunan University of Finance and Economics, Changsha 410000, China
Computer Science and Engineering, Central South University, Changsha 410000, China
References (23)
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