| 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 / / / |
| Reference Info. |
ITE Tech. Rep., vol. 46, no. 6, ME2022-59, pp. 377-381, Feb. 2022. |
| Paper # |
ME2022-59 |
| Date of Issue |
2022-02-14 (MMS, ME, AIT) |
| ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
| Download PDF |
|
| Conference Information |
| Committee |
AIT ME MMS IEICE-IE IEICE-ITS |
| 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) |
|
| Paper Information |
| Registration To |
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 |
| Keyword(6) |
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| Keyword(7) |
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| Keyword(8) |
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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 |
ME |
| Paper # |
MMS2022-34, ME2022-59, AIT2022-34 |
| Volume (vol) |
vol.46 |
| Number (no) |
no.6 |
| Page |
pp.377-381 |
| #Pages |
5 |
| Date of Issue |
2022-02-14 (MMS, ME, AIT) |