Zhuhong Chu1, Jianxun Zhang1,*, Chengdong Wang2, Changhui Yang3
CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1143-1161, 2024, DOI:10.32604/cmc.2024.052269
Abstract Rail fasteners are a crucial component of the railway transportation safety system. These fasteners, distinguished by their high length-to-width ratio, frequently encounter elevated failure rates, necessitating manual inspection and maintenance. Manual inspection not only consumes time but also poses the risk of potential oversights. With the advancement of deep learning technology in rail fasteners, challenges such as the complex background of rail fasteners and the similarity in their states are addressed. We have proposed an efficient and high-precision rail fastener detection algorithm, named YOLO-O2E (you only look once-O2E). Firstly, we propose the EFOV (Enhanced Field… More >
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