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Paper Abstract and Keywords
Presentation 2021-02-19 14:05
[Special Talk] A Note on Discrimination of Road Surface Conditions Based on Deep Learning Using Road Images
Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we study the discrimination of road surface conditions based on deep learning using images captured by fixed-point cameras installed along roads (road surface images). In the case of classifying road surface images into categories corresponding to road surface conditions, there is the problem of imbalanced data since most of the road surface images belong to one category. The proposed method tackles this problem by applying the anomaly detection algorithm to road surface images, which aims to detect a small number of anomalous samples from a large number of normal samples. Then the anomalous sample group consists of road surface images belonging to multiple categories, and detailed classification in addition to anomaly detection can explain the reason why the road surface image is determined to be anomalous. General anomaly detection methods aim to only classify input samples into normal or anomaly categories, and any methods cannot classify detected anomalous samples into detailed categories. Then we propose a novel Classification-Aided Deep Convolutional Autoencoding Gaussian Mixture Model, which can detect anomalous samples and classify them into detailed categories for the discrimination of road surface images. The effectiveness of the model is verified by experiments using road surface images.
Keyword (in Japanese) (See Japanese page) 
(in English) Discrimination of road surface condition / anomaly detection / image classification / imbalanced data / / / /  
Reference Info. ITE Tech. Rep., vol. 45, no. 4, ME2021-21, pp. 165-169, Feb. 2021.
Paper # ME2021-21 
Date of Issue 2021-02-11 (MMS, ME, AIT) 
ISSN Print edition: ISSN 1342-6893  Online edition: ISSN 2424-1970
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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 Discrimination of Road Surface Conditions Based on Deep Learning Using Road Images 
Sub Title (in English)  
Keyword(1) Discrimination of road surface condition  
Keyword(2) anomaly detection  
Keyword(3) image classification  
Keyword(4) imbalanced data  
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1st Author's Name Yuya Moroto  
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
Date Time 2021-02-19 14:05:00 
Presentation Time 10 
Registration for ME 
Paper # ITE-MMS2021-21,ITE-ME2021-21,ITE-AIT2021-21 
Volume (vol) ITE-45 
Number (no) no.4 
Page pp.165-169 
#Pages ITE-5 
Date of Issue ITE-MMS-2021-02-11,ITE-ME-2021-02-11,ITE-AIT-2021-02-11 


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