Nature

A novel PCB surface defect detection method based on separated global context attention to guide residual context aggregation

In the production and manufacturing of Printed Circuit Boards (PCBs), defects can arise negatively impact to both product performance and usability. To tackle the issue of false detections stemming ...
Nature

Enhanced YOLOv11 framework for high precision defect detection in printed circuit boards

This paper presents YOLOv11-PCB, an enhanced deep learning framework specifically designed for automated defect detection in Printed Circuit Boards (PCBs). PCBs are fundamental components in modern ...
Semiconductor Engineering

Identifying PCB Defects with a Deep Learning Single-Step Detection Model

This new technical paper titled “End-to-end deep learning framework for printed circuit board manufacturing defect classification” is from researchers at École de technologie supérieure (ÉTS) in ...