Affiliation:
1. College of Information Science and Engineering, Northeastern University, Shenyang, China
2. China Institute of Arts Science & Technology, Beijing, China
Abstract
In this paper, aiming at the complex background and overlapping characteristics in X-ray images, we propose an unique spatial attention mechanism based on the feedback of high-level semantic feature to guide low-level semantic features, named Feedback Guidance Mechanism (FGM). In addition, in view of the high probability of miss of small prohibited items, a feature aggregation method based on the fusion of high and low-level features and dilated convolution is proposed, named Feature Aggregation Module (FAM). Then, we combine FGM and FAM into a lightweight model SSD and get a new Prohibited Items Detector (PIXDet). Our experiments indicate that PIXDet is more lightweight, but it can achieve 90.36% mAP on PIXray dataset, exceeding SSD by 1.0% mAP, outperforming some state-of-the-art methods, implying its potential applications in prohibited items detection field.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Multi-Scale Dense Detector for Prohibited Items Detection in X-Ray Images;2024 7th International Symposium on Autonomous Systems (ISAS);2024-05-07
2. PID-YOLOX: An X-Ray Prohibited Items Detector Based on YOLOX;2023 IEEE 13th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER);2023-07-11