Distress Detection in Subway Tunnel Images via Data Augmentation Based on Selective Image Cropping and Patching

Distresses, such as cracks, directly reflect the structural integrity of subway tunnels. Therefore, the detection of subway tunnel distress is an essential task in tunnel structure maintenance. This paper presents the performance improvement of deep learning-based distress detection to support the m...

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Detalles Bibliográficos
Autores principales: Maeda, Keisuke, Takada, Saya, Haruyama, Tomoki, Togo, Ren, Ogawa, Takahiro, Haseyama, Miki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9699127/
https://www.ncbi.nlm.nih.gov/pubmed/36433529
http://dx.doi.org/10.3390/s22228932

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9699127/
https://www.ncbi.nlm.nih.gov/pubmed/36433529
http://dx.doi.org/10.3390/s22228932

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