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  • 标题:Research on recognizing required items based on opencv and machine learning
  • 本地全文:下载
  • 作者:Qingyun Ma ; Xubin Huang
  • 期刊名称:SHS Web of Conferences
  • 印刷版ISSN:2416-5182
  • 电子版ISSN:2261-2424
  • 出版年度:2022
  • 卷号:140
  • 页码:1-6
  • DOI:10.1051/shsconf/202214001016
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:Starting from the background of the outbreak of New Coronavirus, in order to realize the function of automatically identifying the required items by machine, the support vector machine algorithm in the neural network and the traditional computer vision algorithm opencv were used. The software developed by pycharm and python programming language was used to compile automatically a software to identify whether the required items were filled out. And on the basis of completing the software, it is connected to the embedded device high-speed clapper. It is applied to Fuzhou Customs to help the customs staff review the health form and declaration card of inbound and outbound passengers, which not only saves the time of staff and passengers, but also contributes to the prevention and control of epidemic situation to a certain extent.
  • 关键词:SVM algorithm;Computer vision;Identification of required items
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