Shuffle-RepNet: A Reparameterized Convolutional Neural Network for Rail Clip State Recognition-Reference-Cited by-同舟云学术

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Shuffle-RepNet: A Reparameterized Convolutional Neural Network for Rail Clip State Recognition

Published:2022-07-25 Issue: Volume: Page:
ISSN:
Container-title:2022 41st Chinese Control Conference (CCC)
language:
Short-container-title:

Author:

Liu Ye¹,Song Bo¹

Affiliation:

1. Jiangsu Normal University, School of Electrical Engineering and Automation,Xuzhou,Jiangsu,221000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9901509/9901494/09902547.pdf?arnumber=9902547

Reference19 articles.

1. Railway fastener state detection based on HOG feature[J];li;Transducer and Microsystem Technologies,2013

2. Automatic detection of defective rail anchors

3. Research on automatic inspection algorithm for railway fastener defects based on computer vision[J];liu;Journal of the china railway society,2016

4. Research and application of automatic detection of rail fastener damage[J];hou;Bulletin of Surveying and Mapping,2021

5. Deep multitask learning for railway track inspection[J];gibert;IEEE Transactions on Pattern Analysis and Machine Intelligence,2017

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1. Railroad missing components detection via cascade region‐based convolutional neural network with predefined proposal templates;Computer-Aided Civil and Infrastructure Engineering;2024-06-04

2. High-speed railway track components inspection framework based on YOLOv8 with high-performance model deployment;High-speed Railway;2024-02

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