An efficient and lightweight detection method for stranded elastic needle defects in complex industrial environments using VEE-YOLO
Deep learning has achieved significant success in the field of defect detection; however, challenges remain in detecting small-sized, densely packed parts under complex working conditions, including occlusion and unstable lighting conditions. This paper introduces YOLOv8-n as the core network to pro...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English English |
| Published: |
Nature Research
2025
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/120220/ http://psasir.upm.edu.my/id/eprint/120220/1/120220.pdf http://psasir.upm.edu.my/id/eprint/120220/2/120220.pdf |