Improved YOLOv5 Network for Steel Surface Defect Detection

Improved YOLOv5 Network for Steel Surface Defect Detection

Steel surface defect detection is crucial for ensuring steel quality. The traditional detection algorithm has low detection probability. This paper proposes an improved algorithm based on the YOLOv5 model to enhance detection probability. Firstly, deformable convolution is introduced in the backbone...

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Bibliographic Details
Main Authors: Bo Huang, Jianhong Liu, Xiang Liu, Kang Liu, Xinyu Liao, Kun Li, Jian Wang
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Metals
Subjects:
YOLOv5
deformable convolution
attention mechanism
<i>Focal EIOU</i>
<i>K-means</i>
Online Access:https://www.mdpi.com/2075-4701/13/8/1439

Internet

https://www.mdpi.com/2075-4701/13/8/1439

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