Deep-Learning Methods for Defect Inspection of Plated Through Holes With Clustering-Based Auto-Labeling and GAN-Based Model Training

Deep-Learning Methods for Defect Inspection of Plated Through Holes With Clustering-Based Auto-Labeling and GAN-Based Model Training

This paper presents the integration of several deep learning techniques for defect inspection of plated through-hole (PTH) on printed circuit boards (PCBs). In our proposed system, the object detection technology of You Only Look Once (YOLO) allocates the position of PTHs; a semi-automatic clusterin...

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Bibliographic Details
Main Authors: Chang-Yeh Hsieh, Ling-Shen Tseng, Yi-Han Chen, Chiung-Hui Tsai, Chih-Hung Wu
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Automated optical inspection (AOI)
defect detection
deep learning
electroplated through-hole (PTH)
printed circuit board (PCB)
generative adversarial network (GAN)
Online Access:https://ieeexplore.ieee.org/document/10792891/
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https://ieeexplore.ieee.org/document/10792891/

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