Detection of Surface Defects in Steel Based on Dual-Backbone Network: MBDNet-Attention-YOLO

Automated surface defect detection in steel manufacturing is pivotal for ensuring product quality, yet it remains an open challenge owing to the extreme heterogeneity of defect morphologies—ranging from hairline cracks and microscopic pores to elongated scratches and shallow dents. Existing approach...

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Bibliographic Details
Main Authors: Xinyu Wang, Shuhui Ma, Shiting Wu, Zhaoye Li, Jinrong Cao, Peiquan Xu
Format: Article
Language:English
Published: MDPI AG 2025-08-01
Series:Sensors
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Online Access:https://www.mdpi.com/1424-8220/25/15/4817
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