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  1. No Access

    Article

    DLF-YOLOF: an improved YOLOF-based surface defect detection for steel plate

    Surface defects can affect the quality of steel plate. Many methods based on computer vision are currently applied to surface defect detection of steel plate. However, their real-time performance and object de...

    Guang-hu Liu, Mao-xiang Chu, Rong-fen Gong… in Journal of Iron and Steel Research Interna… (2024)

  2. No Access

    Article

    Unbalanced classification method using least squares support vector machine with sparse strategy for steel surface defects with label noise

    Least squares support vector machine (LS-SVM) plays an important role in steel surface defects classification because of its high speed. However, the defect samples obtained from the real production line may b...

    Li-ming Liu, Mao-xiang Chu, Rong-fen Gong… in Journal of Iron and Steel Research Interna… (2020)

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    Article

    Multi-class classification method for strip steel surface defects based on support vector machine with adjustable hyper-sphere

    Focusing on strip steel surface defects classification, a novel support vector machine with adjustable hyper-sphere (AHSVM) is formulated. Meanwhile, a new multi-class classification method is proposed. Origin...

    Mao-xiang Chu, ** Liu, Rong-fen Gong… in Journal of Iron and Steel Research Interna… (2018)

  4. No Access

    Article

    Multi-class Classification Methods of Enhanced LS-TWSVM for Strip Steel Surface Defects

    Considering strip steel surface defect samples, a muli-class classicaton method was proposed based on enhanced least squares twin support vector machines (ELS-TWSVMs) and binary tree. Firstly, pruning region s...

    Mao-xiang Chu, An-na Wang, Rong-fen Gong… in Journal of Iron and Steel Research Interna… (2014)