| Paper Abstract and Keywords |
| Presentation |
2021-02-18 11:35
A Note on Accurate Distress Image Classification of Road Structures Using Attention Map based on Text Data
Naoki Ogawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
This paper presents a correlation-aware attention branch network (CorABN) using multi-modal data for deterioration level estimation of infrastructures. CorABN can collaboratively use visual features from distress images and text features from text data recorded at the inspection to improve the estimation accuracy. Specifically, by maximizing the correlation between the visual and text features that provide useful information for the deterioration level estimation, a correlation-aware attention map can be generated. Besides, the text features are also utilized in the final estimation along with visual features improved by the attention mechanism. With the losses based on both the estimation accuracy and the correlation, CorABN can train the entire model in an end-to-end manner. Experiments using distress images and their corresponding text data show the effectiveness of the proposed method. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Distress image / deterioration level estimation / deep learning / correlation maximization / attention map / / / |
| Reference Info. |
ITE Tech. Rep., vol. 45, no. 4, ME2021-4, pp. 17-21, Feb. 2021. |
| Paper # |
ME2021-4 |
| Date of Issue |
2021-02-11 (MMS, ME, AIT) |
| ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
| Download PDF |
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| Conference Information |
| Committee |
IEICE-IE IEICE-ITS MMS ME AIT |
| Conference Date |
2021-02-18 - 2021-02-19 |
| 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 |
ME |
| Conference Code |
2021-02-IE-ITS-MMS-ME-AIT |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
A Note on Accurate Distress Image Classification of Road Structures Using Attention Map based on Text Data |
| Sub Title (in English) |
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| Keyword(1) |
Distress image |
| Keyword(2) |
deterioration level estimation |
| Keyword(3) |
deep learning |
| Keyword(4) |
correlation maximization |
| Keyword(5) |
attention map |
| Keyword(6) |
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| 1st Author's Name |
Naoki Ogawa |
| 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 |
Takahiro Ogawa |
| 3rd Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
| 4th Author's Name |
Miki Haseyama |
| 4th Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2021-02-18 11:35:00 |
| Presentation Time |
25 minutes |
| Registration for |
ME |
| Paper # |
MMS2021-4, ME2021-4, AIT2021-4 |
| Volume (vol) |
vol.45 |
| Number (no) |
no.4 |
| Page |
pp.17-21 |
| #Pages |
5 |
| Date of Issue |
2021-02-11 (MMS, ME, AIT) |