A GAN-based Deep Learning Model for the Object Detection of Autonomous High-Speed Trains-Reference-Cited by-同舟云学术

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A GAN-based Deep Learning Model for the Object Detection of Autonomous High-Speed Trains

Published:2023-11-17 Issue: Volume:47 Page:4393-4398
ISSN:
Container-title:2023 China Automation Congress (CAC)
language:
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Author:

Wang Xinghe¹,Yin Jiateng¹,Pu Fan²,Chen Xing³,D’Ariano Andrea⁴,Tang Tao¹

Affiliation:

1. Beijing Jiaotong University,State Key Laboratory of Advanced Rail Autonomous Operation,Beijing,China,100044

2. Texas A&M University,Zachry Department of Civil and Environmental Engineering,TX,US,77843

3. Nanchang Rail Transit Group Limited Corporation,Nanchang,Jiangxi,China

4. Universitàdegli Studi Roma Tre,Department of Civil, Computer Science and Aeronautical Technologies Engineering,Rome,Italy

Funder

National Natural Science Foundation of China

Beijing Natural Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10450150/10449968/10450584.pdf?arnumber=10450584

Reference15 articles.

1. Data-driven models for train control dynamics in high-speed railways: LAG-LSTM for train trajectory prediction

2. Data-driven approaches for modeling train control models: Comparison and case studies

3. Traffic light detection with color and edge information

4. A vision-based traffic light detection system at intersections;Chung;Journal of National Taiwan Normal University: Mathematics, Science & Technology,2002

5. A robust video based traffic light detection algorithm for intelligent vehicles

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