Journal of Optoelectronics · Laser, Volume. 33, Issue 1, 53(2022)

Cluster analysis of wheel tread defects based on gray-gradient cooccurrence matrix

LIU Erlin1、*, LIU Chenggang1, JIANG Xiangju2, and YANG Shangmei3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    References(3)

    [2] [2] KRUMMENACHER G,CHENG S O,KOLLER S,et al.Wheel defect detection with machine learning[J].IEEE Transactions on Intelligent Transportation Systems,2017,19(4):1176-1187.

    [3] [3] NENOV N,DIMITROV E,VASILEV V,et al.Sensor system of detecting defects in wheels of railway vehicles running at operational speed[C]//34th International Spring Seminar on Electronics Technology,May 11-15,2011,Tratanska Lomnica,Slovakia.New York:IEEE,2011.

    [5] [5] REN S,HE K,GIRSHICK R,et al.Faster R-CNN:towards real-time object detection with region proposal networks[J].IEEE Transactions on Pattern Analysis & Machine Intelligence,2017,39(6):1137-1149.

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    LIU Erlin, LIU Chenggang, JIANG Xiangju, YANG Shangmei. Cluster analysis of wheel tread defects based on gray-gradient cooccurrence matrix[J]. Journal of Optoelectronics · Laser, 2022, 33(1): 53

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    Paper Information

    Received: Apr. 29, 2021

    Accepted: --

    Published Online: Oct. 9, 2024

    The Author Email: LIU Erlin (64546147@qq.com)

    DOI:10.16136/j.joel.2022.01.0291

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