A lightweight steel surface defect detection network based on YOLOv9
In the steel production process, surface defect detection is crucial for ensuring product quality. To address the issues of high computational cost and low detection accuracy in current steel defect detection models, we propose a YOLOv9-based steel defect detection algorithm, CCSS-YOLO. First, we in...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2025-05-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0273824 |
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