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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | en en |
| Published: |
Nature Research
2025
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| Online Access: | http://psasir.upm.edu.my/id/eprint/120220/1/120220.pdf http://psasir.upm.edu.my/id/eprint/120220/2/120220.pdf http://psasir.upm.edu.my/id/eprint/120220/ https://www.nature.com/articles/s41598-025-85721-9?error=cookies_not_supported&code=1cd19737-28e4-478f-a6de-a9518c54d657 |
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