Semantic Segmentation of Railway Infrastructure Based on Virtual Model Synthetic Data-Reference-Cited by-同舟云学术

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Semantic Segmentation of Railway Infrastructure Based on Virtual Model Synthetic Data

Published:2023-09-24 Issue: Volume:11.10 Page:3831-3836
ISSN:
Container-title:2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
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Author:

Yan Bin¹,Wang Sicheng¹,Hu Wenbo²,Liu Xianhua¹,Wang Weidong¹,Liu Yan¹,Wang Jin¹,Qiu Shi¹

Affiliation:

1. Central South University,Department of Civil Engineering,Changsha,Hunan,China,410083

2. The Hong Kong Polytechnic University,Department of Civil and Environmental Engineering,Hong Kong,China,999077

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10420842/10420843/10422077.pdf?arnumber=10422077

Reference22 articles.

1. Three-dimensional reconstruction of structural surface model of heritage bridges using UAV-based photogrammetric point clouds;Yue;Remote Sensing,2019

2. A New Approach for Inspection of Selected Geometric Parameters of a Railway Track Using Image-Based Point Clouds

3. Point cloud semantic segmentation of complex railway environments using deep learning

4. Deep learning-based tree classification using mobile LiDAR data

5. A LiDAR Point Cloud Generator

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Automated detection of pavement distress based on enhanced YOLOv8 and synthetic data with textured background modeling;Transportation Geotechnics;2024-09

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