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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.

Deep-Learning Based Algorithm for Detecting Targets in Infrared Images