Automatic Detection Strategy of Multi-Scale Catenary Support Device Based on Improved YOLOv7

Author:

Jiang Dongzhu,Liu Keyan,Jia Limin,Qin Yong,Jiang Yaopeng,Wang Zhipeng

Funder

State Key Laboratory of Rail Traffic Control and Safety

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

General Medicine

Reference19 articles.

1. Research on Detection Algorithm of Catenary Insulator Based on Improved Faster R-CNN;Hongtao,2020

2. A High-Precision Positioning Approach for Catenary Support Components With Multiscale Difference;Liu;IEEE Transactions on Instrumentation and Measurement,2020

3. Automatic Defect Detection of Fasteners on the Catenary Support Device Using Deep Convolutional Neural Network;Chen;IEEE Transactions on Instrumentation and Measurement,2018

4. A Looseness Detection Method for Railway Catenary Fasteners Based on Reinforcement Learning Refined Localization;Zhong;IEEE Transactions on Instrumentation and Measurement,2021

5. Multi-Objective Performance Evaluation of the Detection of Catenary Support Components Using DCNNs;Liu;IFAC-PapersOnLine,2018

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