Studying the performance of YOLOv11 incorporating DHSA BRA and PPA modules in railway track fasteners defect detection

Abstract With the development of railway transportation and the advancement of deep learning, object detection algorithms are increasingly replacing manual inspection of track fasteners. However, current algorithms struggle with low accuracy in complex weather conditions or low-contrast backgrounds....

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Detalhes bibliográficos

Principais autores:	Chengwei Zhang, Jiawei Zhu, Yihao Ma, Qingmei Huang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2025-07-01
coleção:	Scientific Reports
Assuntos:	Defect detection Deep learning YOLO11 Feature fusion Attention mechanism
Acesso em linha:	https://doi.org/10.1038/s41598-025-13435-z
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