Paper Abstract and Keywords |
Presentation |
2022-02-22 16:45
A Note on Accurate Distress Classification Using Deep Learning Considering Confidence in Attention map Naoki Ogawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
This paper presents a note on accurate distress classification using deep learning considering confidence in attention maps. Specifically, this paper proposes confidence-aware attention branch network (ConfABN), which introduces a confidence-aware attention mechanism that reduces the influence of ineffective attention maps by considering the corresponding confidence in the attention maps. The confidence can be calculated from the entropy of the estimated class probabilities in generating the attention map, and it enables the weighting of feature maps using the effective attention map strongly and the ineffective attention map weakly. ConfABN can effectively utilize the attention mechanism to focus more attention on the regions that are important for the final estimation by considering the confidence. Experiments using images taken during inspections of actual infrastructures verify the effectiveness of the proposed method. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Distress image / deterioration level estimation / deep learning / confidence / attention map / / / |
Reference Info. |
ITE Tech. Rep., vol. 46, no. 6, ME2022-58, pp. 371-376, Feb. 2022. |
Paper # |
ME2022-58 |
Date of Issue |
2022-02-14 (MMS, ME, AIT) |
ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
Download PDF |
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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) |
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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 Accurate Distress Classification Using Deep Learning Considering Confidence in Attention map |
Sub Title (in English) |
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Keyword(1) |
Distress image |
Keyword(2) |
deterioration level estimation |
Keyword(3) |
deep learning |
Keyword(4) |
confidence |
Keyword(5) |
attention map |
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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 |
2022-02-22 16:45:00 |
Presentation Time |
15 minutes |
Registration for |
ME |
Paper # |
MMS2022-33, ME2022-58, AIT2022-33 |
Volume (vol) |
vol.46 |
Number (no) |
no.6 |
Page |
pp.371-376 |
#Pages |
6 |
Date of Issue |
2022-02-14 (MMS, ME, AIT) |