Track Defect Detection Based on Improved Rtmdet

Author:

Fan Rong1ORCID,Sun Qi1ORCID,He Qi1ORCID,Qiao Zhi1ORCID,Chen Hongzhu1ORCID,Zhao Wenqiang1ORCID,Ma Lin1ORCID,Ning Yue1ORCID,Shi Pengfei1ORCID

Affiliation:

1. Hohai University, China

Funder

Jiangsu Province Natural Science Foundation, Grant Number

Changzhou Sci&Tech Program

Key Project of Jiangsu Provincial Key Laboratory of Transmission and Distribution Equipment Technology Team

Publisher

ACM

Reference21 articles.

1. Research on deep learning method for rail surface defect detection;Feng JH;IET Electrical Systems in Transportation,2020

2. Multi task learning for track segmentation and intrusion detection;Zhang S;Computer System Applications,2023

3. Learning Visual Similarity for Inspecting Defective Railway Fasteners

4. Machine vision based missing fastener detection in rail track images using SVM classifier;Manikandan R;International Journal on Smart Sensing and Intelligent Systems,2017

5. Rail Surface Defect Detection Based on An Improved YOLOv5s;Luo H;Applied Sciences,2023

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