Dual-Branch Residual Network for Enhanced Steel Plate Fault Detection

Steel plate fault detection plays a crucial role in industrial manufacturing. However, the inherent complexity of steel plate fault data and the redundancy of certain features pose significant challenges for effective feature extraction. To address these challenges, we propose a dual-branch residual...

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Veröffentlicht in:	Journal of advanced computational intelligence and intelligent informatics Jg. 29; H. 6; S. 1311 - 1318
Hauptverfasser:	Chen, Hao, Lu, Jiaxin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Tokyo Fuji Technology Press Co. Ltd 20.11.2025
Schlagworte:	Accuracy Algorithms Aluminum Artificial neural networks Datasets Fault detection Feature extraction Informatics Machine learning Manufacturing Neural networks Principal components analysis Product reliability Steel plates
ISSN:	1343-0130, 1883-8014
Online-Zugang:	Volltext
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