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Paper Abstract and Keywords
Presentation 2022-02-22 17:00
A Note on Distress Detection based on Deep Learning with Hierarchical Multi-Scale Attention Mechanism for Supporting Maintenance of Subway Tunnels
Saya Takada, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) In maintenance of transportation infrastructures, advanced support technologies that can reduce the burden on engineers and reduce costs are required. In this paper, we propose a new method for distress detection of subway tunnels based on deep learning by introducing multi-scale attention for the purpose of supporting the maintenance of subway tunnels. The state and size of distress in subway tunnels vary widely even within the same subway line. We analyze subway tunnel images in a hierarchical manner with multiple resolutions to accurately detect the distress in consideration of the property of the distress.
Keyword (in Japanese) (See Japanese page) 
(in English) deep learning / distress detection / subway tunnels / maintenance / multi-scale attention / / /  
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Conference Information
Committee IE ITS ITE-AIT ITE-ME ITE-MMS  
Conference Date 2022-02-21 - 2022-02-22 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To ITE-ME 
Conference Code 2022-02-AIT-ME-MMS-IE-ITS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Note on Distress Detection based on Deep Learning with Hierarchical Multi-Scale Attention Mechanism for Supporting Maintenance of Subway Tunnels 
Sub Title (in English)  
Keyword(1) deep learning  
Keyword(2) distress detection  
Keyword(3) subway tunnels  
Keyword(4) maintenance  
Keyword(5) multi-scale attention  
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1st Author's Name Saya Takada  
1st Author's Affiliation Hokkaido University (Hokkaido Univ.)
2nd Author's Name Keisuke Maeda  
2nd Author's Affiliation Hokkaido University (Hokkaido Univ.)
3rd Author's Name Ren Togo  
3rd Author's Affiliation Hokkaido University (Hokkaido Univ.)
4th Author's Name Takahiro Ogawa  
4th Author's Affiliation Hokkaido University (Hokkaido Univ.)
5th Author's Name Miki Haseyama  
5th Author's Affiliation Hokkaido University (Hokkaido Univ.)
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Speaker Author-1 
Date Time 2022-02-22 17:00:00 
Presentation Time 15 minutes 
Registration for ITE-ME 
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Volume (vol) vol.121 
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