Fusion YOLOv8s and Dynamic Convolution Algorithm for Steel Surface Defect Detection

The detection of surface defects in steel is a prerequisite for improving steel quality. When detecting surface defects in steel, the texture features of defective areas often show significant differences from the symmetry patterns of normal areas. To address the issues of low accuracy and slow reco...

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Bibliographic Details

Published in:	Symmetry (Basel) Vol. 17; no. 5; p. 701
Main Authors:	Huang, Chunyan, Cui, Jingnan, Li, Yanling, Lu, Yao, Yang, Chunyu
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 04.05.2025
Subjects:	Accuracy Algorithms Boxes Classification Convolution Datasets Defects Feature extraction Localization Modules Neural networks Real time Steel Surface defects Surface layers
ISSN:	2073-8994, 2073-8994
Online Access:	Get full text
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