Accurate Detection of Catenary Support Components with Few Samples Based on Meta-Learning
ID:149 View Protection:ATTENDEE Updated Time:2025-11-03 11:13:21 Hits:254 Poster Presentation

Start Time:2025-11-09 09:09(Asia/Shanghai)

Duration:1min

Session:P Poster presentation » P77.Electric Machine Design and Control

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Abstract
The high-speed railway catenary system is a critical component of railway infrastructure, and any malfunction can cause serious harm. However, due to the complex structure of the catenary system, it is difficult to ensure that all samples in each section will be labeled, which makes it difficult to locate and detect some small sample components. Therefore, this paper proposes a small sample catenary component detection method based on meta-learning. This method can effectively detect unlabeled special segment samples.
Keywords
High-speed rail, Catenary, Few Samples, Meta-Learning
Speaker
Wenqiang Liu
The Hong Kong Polytechnic University

Submission Author
文强 刘 香港理工大学
琳珺 时 西南交通大学
皓楠 杨 西南交通大学
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Important Date
  • Conference Date

    Nov 07

    2025

    to

    Nov 09

    2025

  • Oct 30 2025

    Draft paper submission deadline

  • Nov 10 2025

    Registration deadline

Sponsored By
IEEE西南交通大学IAS学生分会
Organized By
西南交通大学电气工程学院
SPACI车网关系研究室
四川大学电力系统稳定与高压直流输电研究团队