ISRM: introspective self-supervised reconstruction model for rail surface defect detection and segmentation
Yaxing Li,
Yongzhi Min,
Biao Yue
Abstract:The problems of intrinsic imbalance of the sample and interference from complex backgrounds limit the performance of existing deep learning methods when applied to the detection and segmentation of rail surface defects. To address these issues, an introspective self-supervised reconstruction model (ISRM) is proposed, which only requires normal samples in the training phase and incorporates the concept of self-supervised learning into an introspective autoencoder. The training framework of ISRM first extracts g… Show more
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