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  • 标题:Defect detection on videos using neural network
  • 本地全文:下载
  • 作者:Roman Sizyakin ; Nikolay Gapon ; Igor Shraifel
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2017
  • 卷号:132
  • 页码:1-5
  • DOI:10.1051/matecconf/201713205014
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:In this paper, we consider a method for defects detection in a video sequence, which consists of three main steps; frame compensation, preprocessing by a detector, which is base on the ranking of pixel values, and the classification of all pixels having anomalous values using convolutional neural networks. The effectiveness of the proposed method shown in comparison with the known techniques on several frames of the video sequence with damaged in natural conditions. The analysis of the obtained results indicates the high efficiency of the proposed method. The additional use of machine learning as postprocessing significantly reduce the likelihood of false alarm.
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