Semi-Conv-DETR: A railway ballast bed defect detection model integrating convolutional augmentation and semi-supervised DETR-Reference-Cited by-同舟云学术

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Semi-Conv-DETR: A railway ballast bed defect detection model integrating convolutional augmentation and semi-supervised DETR

Published:2024-09 Issue: Volume:48 Page:101334
ISSN:2214-3912
Container-title:Transportation Geotechnics
language:en
Short-container-title:Transportation Geotechnics

Author:

Teng Jing,Long Xujie,Yang Qi,Jing Guoqing,Liu Huan

Publisher

Elsevier BV

Reference35 articles.

1. State-of-the-art review of ground penetrating radar (gpr) applications for railway ballast inspection;Wang;Sensors,2022

2. Critical speed of ballasted railway tracks: Influence of ballast and subgrade degradation;Malisetty;Transp Geotech,2024

3. Railway subgrade defect automatic recognition method based on improved faster r-cnn;Xu;Scientific Programm,2018

4. Overview on safety management and maintenance of high-speed railway in china;Lu;Transp Geotech,2020

5. Railway track condition assessment at network level by frequency domain analysis of gpr data;Fontul;Remote Sens,2018

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