• Infrared Technology
  • Vol. 44, Issue 12, 1351 (2022)
He LIU1, Tiancheng ZHAO1, Junbo LIU1, Lixin JIAO1, Zhihao XU2, and Xiaocui YUAN2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: Cite this Article
    LIU He, ZHAO Tiancheng, LIU Junbo, JIAO Lixin, XU Zhihao, YUAN Xiaocui. Deep Residual UNet Network-based Infrared Image Segmentation Method for Electrical Equipment[J]. Infrared Technology, 2022, 44(12): 1351 Copy Citation Text show less
    References

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

    [6] Rahmani A, Haddadnia J, SeryasatO. Intelligent fault detection of electrical equipment in ground substations using thermo vision technique[C]//2010 2nd International Conference on Mechanical and Electronics Engineering, 2010: V2-150-V2-154.

    [7] LIN K C, LAI C S. Fault recognition system of electrical components in scrubber using infrared images[C]//International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, 2003: 1303-1310.

    [17] CHEN Z, ZHU H. Visual quality evaluation for semantic segmentation: subjective assessment database and objective assessment measure[J]. IEEE Transactions on Image Processing, 2019, 28(12): 5785-5796.

    LIU He, ZHAO Tiancheng, LIU Junbo, JIAO Lixin, XU Zhihao, YUAN Xiaocui. Deep Residual UNet Network-based Infrared Image Segmentation Method for Electrical Equipment[J]. Infrared Technology, 2022, 44(12): 1351
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