PCB plug-in solder joint defect detection method based on coordinated attention-guided information fusion

Author:

Chen Wenbin,Wang Zheng,Zhao Hongchao

Funder

School-level project of Chongqing University of Science and Technology

the Science and Technology Research Program Project of Chongqing Municipal Education Commission

Deep Learning Based Online Detection of Assembly Defects in Printed Circuit Board Components

Publisher

Springer Science and Business Media LLC

Reference30 articles.

1. Yuan, Y. & Tan, X. Defect detection of refrigerator metal surface in complex environment. J. Comput. Appl. 41, 270–274 (2021).

2. Yi, K. F., Hu, J., Cui, K. Y. & Hu, H. W. Surface defect detection of Copper clad laminates based on secondary feature screening. Modem Manuf. Eng. 6, 95–100 (2021).

3. Zhang, T., Liu, Y. T., Yang, Y. N., Wang, X. & Jin, Y. G. Review of surface defect detection based on machine vision. Sci. Technol. Eng. 20, 14366–14376 (2020).

4. Szymanski, C., Stemmer, M.R. Automated PCB inspection in small series production based on SIFT algorithm. In Proceedings of the 24th IEEE International Symposium on Industrial Electronics (ISIE 2015), Buzios, Rio de Janeiro, Brazil, 3–5 June 2015

5. Lowe, G. Sift-the scale invariant feature transform. Int. J. 2, 91–110 (2004).

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