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Paper Abstract and Keywords
Presentation 2022-02-21 13:15
A Note on Improvement of Accuracy in Classification of Distress Images for Efficient Inspection of Road Structures -- Introduction of Ratio of Similar Cases Based on Text Data --
Taisei Hirakawa, Naoki Ogawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose a method for correcting the results of distress image classification using text data recorded during the inspection. In the proposed method, the combination of the text data and the deterioration level of the target image is analyzed to see whether the combination of the text data and the result of the target image is different from the past trend. If it is different from the past trend, we set a threshold for the content of text data that are similar to the text data of the target image, and narrow down the candidates for correction. Finally, we correct the classification results by using the correction candidates as the classification results. In the last part of this paper, we demonstrate the effectiveness of the proposed method through experiments using actual distress images and their corresponding text data for several distress image classification methods.
Keyword (in Japanese) (See Japanese page) 
(in English) Distress image / Deterioration classification / Text data / / / / /  
Reference Info. ITE Tech. Rep., vol. 46, no. 6, ME2022-33, pp. 43-48, Feb. 2022.
Paper # ME2022-33 
Date of Issue 2022-02-14 (MMS, ME, AIT) 
ISSN Print edition: ISSN 1342-6893  Online edition: ISSN 2424-1970
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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) 
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 Improvement of Accuracy in Classification of Distress Images for Efficient Inspection of Road Structures 
Sub Title (in English) Introduction of Ratio of Similar Cases Based on Text Data 
Keyword(1) Distress image  
Keyword(2) Deterioration classification  
Keyword(3) Text data  
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1st Author's Name Taisei Hirakawa  
1st Author's Affiliation Hokkaido University (Hokkaido Univ.)
2nd Author's Name Naoki Ogawa  
2nd Author's Affiliation Hokkaido University (Hokkaido Univ.)
3rd Author's Name Keisuke Maeda  
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
Date Time 2022-02-21 13:15:00 
Presentation Time 15 
Registration for ME 
Paper # ITE-MMS2022-8,ITE-ME2022-33,ITE-AIT2022-8 
Volume (vol) ITE-46 
Number (no) no.6 
Page pp.43-48 
#Pages ITE-6 
Date of Issue ITE-MMS-2022-02-14,ITE-ME-2022-02-14,ITE-AIT-2022-02-14 


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