Laser & Optoelectronics Progress, Volume. 61, Issue 18, 1812003(2024)

Defect Detection of Spray Printed Variable Color 2D Code Based on ResNet34-TE

Ying Li, Yao Dong*, Zifen He, Hao Yuan, Fuyang Sun, and Lingxi Gong
Author Affiliations
  • Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, Yunnan, China
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    References(31)

    [3] Wang X H, Chen H. Generation parameter optimization of color QR code based on jet printing technology[J]. Packaging Engineering, 39, 199-203(2018).

    [14] Wu J, Pang W T, Wang L et al. Micro-expression recognition algorithm based on graph convolutional network and Transformer model[J]. High Technology Letters, 29, 213-222(2023).

    [20] Zhu C J, Liu R G, Cheng J W et al. Hybrid defect detection model based on SimAM module and ResNet34 network[J]. Modern Manufacturing Engineering, 1-9(2023).

    [23] Yang X D. Research on metallographic organization classification and identification based on ViT[J]. Electronic Technology & Software Engineering, 154-158(2022).

    [30] Tang D L, Zhou L, Wu X L et al. Study on CNN coupled PCA-DT model for recognition of metal defect[J]. Mechanical Science and Technology for Aerospace Engineering, 41, 1420-1427(2022).

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    Ying Li, Yao Dong, Zifen He, Hao Yuan, Fuyang Sun, Lingxi Gong. Defect Detection of Spray Printed Variable Color 2D Code Based on ResNet34-TE[J]. Laser & Optoelectronics Progress, 2024, 61(18): 1812003

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Dec. 22, 2023

    Accepted: Jan. 29, 2024

    Published Online: Sep. 14, 2024

    The Author Email: Yao Dong (1823101813@qq.com)

    DOI:10.3788/LOP232723

    CSTR:32186.14.LOP232723

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