A Survey of PCB Defect Detection Algorithms
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s10836-023-06091-6.pdf
Reference51 articles.
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2. Adibhatla VA, Shieh J-S, Abbod MF, Chih H-C, Hsu C-C, Cheng J (2018) Detecting defects in PCB using deep learning via convolution neural networks. In: 2018 Proc. 13th International Microsystems, Packaging, Assembly and Circuits Technology Conference (IMPACT). IEEE, pp 202–205
3. Anitha D, Rao M (2019) SMT Component Inspection in PCBA’s using image processing techniques. International Journal of Innovative Technology and Exploring Engineering (IJITEE) 8(12):541–547
4. Bonello D, Iano Y, Neto U (2020) A novel approach to the PCBA’s defects detection using background algorithm. Int J Electr Comput Eng 8:308–315
5. Chaudhary V, Dave IR, Upla KP (2017) Automatic visual inspection of printed circuit board for defect detection and classification. In: Proc. 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET). IEEE, pp 732–737
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