Abstract
Security inspection is an important measure to ensure public safety. At present, X-ray security inspection equipment is widely used in security checkpoints. However, it is not efficient to recognize prohibited items in X-ray images manually. Automated security inspection system has become the development trend of security field. In this paper, the Yolov4 detector was used to detect prohibited items in X-ray images. In order to improve the detection performance, we added CBAM attention modules to different parts of Yolov4. A public dataset is used for simulation experiments, which shows that the addition of CBAM can effectively improve the detection performance of the detector.
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