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Physics-informed semi-supervised learning for hot-rolled strip flatness pattern recognition based on FixMatch method
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DOI：10.1016/j.eswa.2025.128885.png)
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Abstract
En 中文
• An SSL framework is established for hot-rolled strip defect pattern recognition. • A feature extraction method guided by physical information is proposed for SFPR. • FixMatch model is applied in the field of hot rolling SFPR. • PINN method can enhance the accuracy and generalization of SSL framework.
Journal
IF:
7.5
Papers:
3.0W
Citations:
10.2W
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