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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Vydané v:	Journal of advanced computational intelligence and intelligent informatics Ročník 29; číslo 6; s. 1311 - 1318
Hlavní autori:	Chen, Hao, Lu, Jiaxin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Tokyo Fuji Technology Press Co. Ltd 20.11.2025
Predmet:	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
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