OPTICS & OPTOELECTRONIC TECHNOLOGY, Volume. 22, Issue 1, 60(2024)

A Lightweight Ground Wire Defect Detection Method Based on LSD and Deep Learning

WANG Yong-qiang1, ZHOU Xue-ming2, ZHANG Zheng1, LEI Bo1, and WANG Chen-sheng1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • show less
    References(4)

    [1] [1] Nguyen V N,Jenssen R,Roverso D. Automatic autonomous vision-based power line inspection:a review of current status and the potential role of deep learning[J]. International Journal of Electrical Power & Energy Systems,2018,99(7):107-120.

    [2] [2] Campoy P,Correa J F,Ivan Mondragón,et al. Computer vision onboard UAVs for civilian tasks[J]. Journal of Intelligent & Robotic Systems,2008,54(1-3):105-135.

    [3] [3] Pagnano A,Hopf M,Teti R A. Roadmap for automated power line inspection maintenance and repair[C]//International Academy for Production Engineering International Conference on Intelligent Computation in Manufacturing Engineering,2014.

    [12] [12] Howard A,Sandler M,Chu G,et al. Searching for MobileNetV3[J]. 2019.DOI:10.48550/arXiv.1905.02244.

    Tools

    Get Citation

    Copy Citation Text

    WANG Yong-qiang, ZHOU Xue-ming, ZHANG Zheng, LEI Bo, WANG Chen-sheng. A Lightweight Ground Wire Defect Detection Method Based on LSD and Deep Learning[J]. OPTICS & OPTOELECTRONIC TECHNOLOGY, 2024, 22(1): 60

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Received: Nov. 9, 2023

    Accepted: --

    Published Online: Apr. 29, 2024

    The Author Email:

    DOI:

    CSTR:32186.14.

    Topics