• Laser & Optoelectronics Progress
  • Vol. 58, Issue 20, 2014001 (2021)
Lujun Cui, Haiyang Li, Shirui Guo*, Xiaolei Li, Yinghao Cui, Bo Zheng, and Manying Sun
Author Affiliations
  • School of Mechanical and Electrical Engineering, Zhongyuan University of Technology, Zhengzhou, Henan 450007, China
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    DOI: 10.3788/LOP202158.2014001 Cite this Article Set citation alerts
    Lujun Cui, Haiyang Li, Shirui Guo, Xiaolei Li, Yinghao Cui, Bo Zheng, Manying Sun. Laser Cladding Cracks Recognition Based on Deep Learning Combined Convolutional Block Attention Module[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2014001 Copy Citation Text show less
    Improved U-net structure
    Fig. 1. Improved U-net structure
    CBAM layer for increasing feature map training weight information
    Fig. 2. CBAM layer for increasing feature map training weight information
    Channel attention model structure
    Fig. 3. Channel attention model structure
    Spatial attention model structure
    Fig. 4. Spatial attention model structure
    Crack morphologies at different magnifications. (a) 50 times; (b) 100 times; (c) 200 times; (d) 500 times
    Fig. 5. Crack morphologies at different magnifications. (a) 50 times; (b) 100 times; (c) 200 times; (d) 500 times
    Test effect. (a)(b) Image to be tested; (c)(d) manual labeling; (e)(f) neural network labeling; (g)(h) adaptive threshold method labeling
    Fig. 6. Test effect. (a)(b) Image to be tested; (c)(d) manual labeling; (e)(f) neural network labeling; (g)(h) adaptive threshold method labeling
    Expert markPrediction
    TrueFalse
    TrueTrue Positive (TP)False Negative (FN)
    FalseFalse Positive (FP)True Negative (TN)
    Table 1. Confusion matrix
    PositionNone191,98,91,8,97,8,96,7,8,9
    Parameters19411051941368194136819416311942051194231419443421952921
    Accuracy /%77.176.978.779.279.779.179.879.8
    Table 2. Influence of the position of CBAM on the training parameter quantity and accuracy
    Lujun Cui, Haiyang Li, Shirui Guo, Xiaolei Li, Yinghao Cui, Bo Zheng, Manying Sun. Laser Cladding Cracks Recognition Based on Deep Learning Combined Convolutional Block Attention Module[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2014001
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