Abstract: This paper presents an automated Printed Circuit Board (PCB) defect detection system leveraging the YOLOv8 deep learning architecture. The model is designed to accurately detect and classify ...

A curated and enhanced dataset for PCB defect detection with 6 common manufacturing defects. This dataset is cleaned, corrected, and optimized for machine learning research.

This project implements and compares two YOLOv12 object-detection pipelines for printed-circuit-board (PCB) defect identification. The objective is to detect four major defect types: ...

To address the issues of missed detection and false detection during the defect inspection process of the PCB, an improved YOLOv7-based algorithm for PCB defect detection is proposed. Firstly, the ...