DDR-YOLO: An Efficient Detection Model Based on YOLO11s for Steel Surface Defect

In the process of steel production, surface defects on the product are inevitable. Due to challenges such as high surface reflectivity and significant variation in defect scales on steel strips, this paper proposes an improved YOLO11-based algorithm to enhance the accuracy of steel surface defect de...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Xiaoguang Ren, Zhendong Liu, Hui Cheng, Lidong Chen
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Subjects:	Deep learning defect detection attention mechanism feature fusion re-parameterized
Online Access:	https://ieeexplore.ieee.org/document/11129104/