计算机科学与探索2024，Vol.18Issue(5)：1259-1270,12.DOI:10.3778/j.issn.1673-9418.2301041
基于反向瓶颈和LCBAM设计的X光违禁品检测
X-ray Prohibited Items Detection Based on Inverted Bottleneck and Light Convo-lution Block Attention Module
摘要
Abstract
To resolve the problems of position and angle change causing miss and false detection,low accuracy of difficult samples in X-ray luggage images,using YOLOv5 as the baseline,this paper proposes a model by inverted bottleneck and light convolution block attention module for the X-ray prohibited items detection.The inverted bottle-neck design is introduced in the backbone to emphasize the detailed features and improve the model to cope with the large-angle change problem.The light convolution block attention module is used to suppress background interference and reduce model parameter.The Gaussian error linear unit activation function and improved loss function are used to enhance the nonlinear expression ability,increasing the punishment of predicted value to optimize the model's detec-tion ability for difficult samples.The proposed model is trained and tested on three large public datasets OPIXray,SIXray,and HiXray,resulting in the mAP of 91.9%,93.4%,and 82.2%,respectively.The results show that the proposed method can effectively solve the problem of angel change in X-ray luggage,indicating its high accuracy and robustness.关键词
X光图像/违禁品检测/反向瓶颈/轻量化卷积块注意力模块(LCBAM)Key words
X-ray imagery/prohibited items detection/inverted bottleneck/light convolution block attention mod-ule(LCBAM)分类
信息技术与安全科学引用本文复制引用
董乙杉,郭靖圆,李明泽,孙嘉傲,卢树华..基于反向瓶颈和LCBAM设计的X光违禁品检测[J].计算机科学与探索,2024,18(5):1259-1270,12.基金项目
公安部科技强警基础专项(2021JC03) （2021JC03）
中央高校基本科研业务费重大项目(21JKF102). This work was supported by the Police Project of Science and Technology to Strengthen the Basic Work of Ministry of Public Security of China(2021JC03),and the Fundamental Research Funds for the Central Universities of China(21JKF102). （21JKF102）
