The dataset is already organized in YOLO format in the steel_dataset/ directory. If you need to reorganize from original format, see utility/reorganize_dataset.py. steel-defect-detection/ ├── ...

Machine learning enables real-time PCB defect detection using a FOMO model on a Raspberry Pi. Learn how with this ...

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: ...

Abstract: Printed circuit board (PCB) surface defect detection is crucial for ensuring product quality and improving production efficiency. In recent years, deep learning-based methods have achieved ...

Abstract: The focus of this research is to use deep learning models to advance PCB (printed circuit board) panel defect detection in industrial manufacturing, in particular to evaluate and compare the ...