Improving PCB defect detection using selective feature attention and pixel shuffle pyramid

Improving PCB defect detection using selective feature attention and pixel shuffle pyramid

– Due to the ongoing miniaturization of electronic products and the use of miniature printed circuit boards (PCBs), existing AI-based defect detection methods have exhibited poor performance in detecting tiny PCB defects. This issue can potentially compromise safety, degrade manufacturing quality, a...

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Bibliographic Details
Main Authors: Ka Chun Fung, Kai-Wen Xue, Cheung-Ming Lai, Kwan-Ho Lin, Kin-Man Lam
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Results in Engineering
Subjects:
PCB defect detection
Convolution neural network
Multiscale feature fusion
Object detection
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123024002457

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http://www.sciencedirect.com/science/article/pii/S2590123024002457

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