| 基于跨层网络的危险物品X射线自动识别 |
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| 引用本文： | 郭鹏程,张文琪,李毅红. 基于跨层网络的危险物品X射线自动识别[J]. 科学技术与工程, 2020, 20(33): 13718-13724 |
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| 作者姓名： | 郭鹏程 张文琪 李毅红 |
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| 作者单位： | 山西省科学技术厅信息中心,太原030051;中北大学,信息探测与处理山西省重点实验室,太原030051 |
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| 基金项目： | 国家自然科学基金（61801437），山西省自然科学基金（201801D221206，201801D221207） |
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| 摘 要： | 针对当前的行李物品安检系统通过人眼进行判别，检测效率较低、存在漏检的问题。提出了一种改进后的faster-rcnn跨层检测网络，通过跨层连接网络层，采集多种角度下的危险物信息，将网络结构中提取的低层次特征和高层次特征相结合来训练网络结构，提升网络的复杂性。研究表明该方法在本文所构建的数据集上进行训练和检测实验，结果表明检测效果良好。
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| 关 键 词： | X射线检测 卷积神经网络 跨层网络 目标检测 危险物品 |
| 收稿时间： | 2019-11-17 |
| 修稿时间： | 2020-09-16 |
Research on X-ray automatic identification method of dangerous goods based on cross-layer network |
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| GUO Peng-cheng,ZHANG Wen-qi,LI Yi-hong. Research on X-ray automatic identification method of dangerous goods based on cross-layer network[J]. Science Technology and Engineering, 2020, 20(33): 13718-13724 |
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| Authors: | GUO Peng-cheng ZHANG Wen-qi LI Yi-hong |
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| Affiliation: | Shanxi Provincial Department of Science and Technology Information Center,Taiyuan;Shanxi Provincial Key Laboratory of Information Detection and Processing,North University of China,Taiyuan |
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| Abstract: | The current baggage and article security inspection system uses human eyes to judge, the detection efficiency is low, and there are problems of missed inspections. An improved faster-rcnn cross-layer detection network is proposed, which connects the network layers across layers, collects dangerous object information from multiple angles, and combines the low-level features and high-level features extracted from the network structure to train the network Structure to increase the complexity of the network. Research shows that the method is trained and tested on the data set constructed in this paper, and the results show that the detection effect is good. |
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| Keywords: | X-ray detection CNN cross-layer network target detection dangerous goods |
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