Infrared Technology, Volume. 46, Issue 11, 1325(2024)

Fault Detection and Identification of Multi-Source Insulators Based on Improved YOLOv7

Xu LI1,2, Zhiyun XIAO1,2、*, Yedong JIANG1, Yazhou WANG1, and Yu SU1
Author Affiliations
  • 1School of Electric Power, Inner Mongolia University of Technology, Hohhot 010080, China
  • 2Key Laboratory of Electromechanical Control, Hohhot 010051, China
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    References(5)

    [8] [8] HU S, ZHAO F, LU H, et al. Improving YOLOv7-tiny for infrared and visible light image object detection on drones[J]. Remote Sensing, 2023, 15(13): 3214.

    [12] [12] WANG R, LIANG F, MOU X, et al. Development of an improved YOLOv7-based model for detecting defects on strip steel surfaces[J]. Coatings, 2023, 13(3): 536.

    [14] [14] Howard A, Sandler M, Chu G, et al. Searching for mobilenetv3[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019: 1314-1324.

    [20] [20] ZHANG Y F, REN W, ZHANG Z, et al. Focal and efficient IOU loss for accurate bounding box regression[J]. Neurocomputing, 2022, 506: 146-157.

    [22] [22] ZHU X, HU H, LIN S, et al. Deformable convnets v2: More deformable, better results[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019: 9308-9316.

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    LI Xu, XIAO Zhiyun, JIANG Yedong, WANG Yazhou, SU Yu. Fault Detection and Identification of Multi-Source Insulators Based on Improved YOLOv7[J]. Infrared Technology, 2024, 46(11): 1325

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    Paper Information

    Category:

    Received: Oct. 20, 2023

    Accepted: Jan. 10, 2025

    Published Online: Jan. 10, 2025

    The Author Email: Zhiyun XIAO (xiaozhiyun@imut.edu.cn)

    DOI:

    CSTR:32186.14.

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