文章基本信息

标题：Detection of Contraband in Milk Powder Cans by Using Stacked Auto-Encoders Combination with Support Vector Machine
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作者：Yuping Zhu ; Lei Wang ; Wei Zhang 等
期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2018
卷号：170
期号：3
页码：032114
DOI：10.1088/1755-1315/170/3/032114
语种：English
出版社：IOP Publishing
摘要：The carrying of contraband has brought increasingly serious harm to people's lives. At present, detection devices used in important places such as customs, airports and railway stations can not automatically identify contraband, and the final identification is entirely done by hand. Therefore, all countries have devoted a great deal of manpower and material resources to studying and developing more effective contraband detection technologies. In this article, we propose a model based on the stacked auto-encoders (SAE) method to detect contraband in milk powder cans. Firstly, we construct a representative of the majority of the reality of the milk CT image data set, secondly, we use the SAE method to extract the features, and finally use the support vector machine (SVM) classifier to determine whether the contracted product is carried in the milk powder cans. In order to prevent the data from over fitting, in the experiment we used the 5-fold cross-validation method. In addition, we also use the grid method to adjust the parameters of SVM. The excellent experimental results show that the model we proposed has a good effect on the detection of carrying contraband in milk powder cans.