BIOENGINEER

Lightweight EDGI-YOLO improves steel surface defect detection in image-based benchmark study

A benchmark study found that EDGI-YOLO improved [email protected] by 3.94 percentage points over YOLOv8n on NEU-DET while reducing ...
BIOENGINEER

CDA-YOLO improves PCB defect detection over YOLOv11

An enhanced YOLOv11 model developed for printed circuit board inspection achieved mean average precision of 96.1% at an ...
Semiconductor Engineering

Refining Vision-Language Models For Lithography Defect Detection

“Semiconductor lithography inspection requires reliable detection of small pattern defects such as bridge, burr, pinch, and contamination. In this study, we propose a two-stage vision-language ...

Physical AI in manufacturing: How computer vision, robotics and edge automation are moving ...

Physical AI is taking artificial intelligence beyond software and into factories, hospitals and other real-world environments ...