Rust Detection of Power Equipment Based on Mask R-CNN
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    Abstract:

    The recognition of rust target on power equipment has very high application value in power security, nevertheless, the rust has the characteristics of irregular size and shape, thus the detection efficiency and accuracy of traditional machine learning algorithm are not high. Aiming at this problem, the characteristics of rust stain are studied and analyzed, and a rust detection and recognition method for power equipment based on Mask R-CNN is proposed. Faster R-CNN is used to complete the function of target detection, FCN accurately completes the function of semantics segmentation, realizes the classification and recognition at the pixel level, and better solves the problem of irregular rust detection. The experimental results show that the accuracy of rust detection of power equipment based on Mask R-CNN is high.

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薛冰.基于Mask R-CNN的电力设备锈迹检测.计算机系统应用,2019,28(5):248-251

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History
  • Received:December 03,2018
  • Revised:December 25,2018
  • Adopted:
  • Online: May 05,2019
  • Published: May 15,2019
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