Semi-Supervised Deep Learning in High-Speed Railway Track Detection Based on Distributed Fiber Acoustic Sensing

High deployment costs, safety risks, and time delays restrict traditional track detection methods in high-speed railways. Therefore, approaches based on optical sensors have become the most remarkable strategy in terms of deployment cost and real-time performance. Owing to the large amount of data o...

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Detalles Bibliográficos
Autores principales: Wang, Shulun, Liu, Feng, Liu, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8779117/
https://www.ncbi.nlm.nih.gov/pubmed/35062373
http://dx.doi.org/10.3390/s22020413

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8779117/
https://www.ncbi.nlm.nih.gov/pubmed/35062373
http://dx.doi.org/10.3390/s22020413

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