ResNet-SE-CBAM Siamese Networks for Few-Shot and Imbalanced PCB Defect Classification

ResNet-SE-CBAM Siamese Networks for Few-Shot and Imbalanced PCB Defect Classification

Defect detection in mass production lines often involves small and imbalanced datasets, necessitating the use of few-shot learning methods. Traditional deep learning-based approaches typically rely on large datasets, limiting their applicability in real-world scenarios. This study explores few-shot...

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Bibliographic Details
Main Authors: Chao-Hsiang Hsiao, Huan-Che Su, Yin-Tien Wang, Min-Jie Hsu, Chen-Chien Hsu
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Sensors
Subjects:
defect detection
imbalanced datasets
few-shot learning
Siamese networks
Automatic Optical Inspection
Online Access:https://www.mdpi.com/1424-8220/25/13/4233
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