Surface defect detection of steel based on improved YOLOv5 algorithm
To address the challenge of achieving a balance between efficiency and performance in steel surface defect detection, this paper presents a novel algorithm that enhances the YOLOv5 defect detection model. The enhancement process begins by employing the K-means++ algorithm to fine-tune the location o...
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| Format: | Article |
| Language: | English |
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AIMS Press
2023-11-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2023879?viewType=HTML |