Laser & Infrared, Volume. 55, Issue 3, 399(2025)

An accurate segmentation method for infrared image of electrical equipment under complex environment

WANG Qi1, ZHANG Xin-wei2, TONG Yue1, WANG Yu-qing1, ZHANG Jin1, WANG Yong-tao3, and YUAN Xiao-cui3
Author Affiliations
  • 1China Electric Power Research Institute Co., Ltd., Wuhan 430074, China
  • 2China North China Electric Power University (Baoding), Baoding 071003, China
  • 3Nanchang Institute of Technology, Nanchang 330099, China
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    References(4)

    [3] [3] H Zou, F Huang. A novel intelligent fault diagnosis method for electrical equipment using infrared thermography[J]. Infrared Physics & Technology, 2015, 73: 29-35.

    [11] [11] Ou J, Wang J, Xue J, et al. Infrared image target detection of substation electrical equipment using an improved faster R-CNN[J]. IEEE Transactions on Power Delivery, 2023, 38(1): 387-396.

    [15] [15] H Zhao, J Shi, X Qi, et al. Pyramid scene parsing network[C]//2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017: 6230-6239.

    [16] [16] S Woo, J Park, J Y. Lee, et al. CBAM: Convolutional block attention module[C]//In Proceedings of the European Conference on Computer Vision (ECCV), 2018: 3-19.

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    WANG Qi, ZHANG Xin-wei, TONG Yue, WANG Yu-qing, ZHANG Jin, WANG Yong-tao, YUAN Xiao-cui. An accurate segmentation method for infrared image of electrical equipment under complex environment[J]. Laser & Infrared, 2025, 55(3): 399

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    Paper Information

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    Received: Apr. 29, 2024

    Accepted: Apr. 23, 2025

    Published Online: Apr. 23, 2025

    The Author Email:

    DOI:10.3969/j.issn.1001-5078.2025.03.012

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