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Xiaofeng Yao

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Conference Aug 2026

Improved YOLOv5s rail tiny defect detection method integrating CA attention mechanism and transposed convolution

To address challenges in railway defect detection including difficult feature extraction, low small-target detection accuracy, and complex background interference, this paper proposes an enhanced YOLOv5s-based model named CA-TC-YOLOv5s. First, a coordinate attention (CA) mechanism is integrated into the backbone's C3 m...

Xiaofeng Yao, Fu-Jie Huang · 0 citations

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