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Paper Abstract and Keywords
Presentation 2018-03-19 15:35
Accuracy Improvement of Fashon Style Classification by Appropriate Training Data and Estimation of Human Regions
Takeshi Nakajima, Takuro Oki, Ryusuke Miyamoto (Meiji Univ.) EA2017-137 SIP2017-146 SP2017-120
Abstract (in Japanese) (See Japanese page) 
(in English) Fashion style estimation from an input image where a human wearing clothes exists is a challenging task in the field of image recognition. This paper tries to improve the classification accuracy of fashion style estimation by the following two approaches: construction of an appropriate data set with style labels and preprocessing with semantic segmentation to reduce the influence of background regions. The data set constructed in this work improved the classification accuracy of the Hipster Wars data set to about 78.8%. When the semantic segmentation based on PSPNet was applied with our data set, the classification accuracy was improved to about 80.9% that is currently the best accuracy in the world.
Keyword (in Japanese) (See Japanese page) 
(in English) Fashion style estimation / large-scale data set / deep neural network / semantic segmentation / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 516, SIP2017-146, pp. 197-202, March 2018.
Paper # SIP2017-146 
Date of Issue 2018-03-12 (EA, SIP, SP) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF EA2017-137 SIP2017-146 SP2017-120

Conference Information
Committee SIP EA SP MI  
Conference Date 2018-03-19 - 2018-03-20 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech, Engineering/Electro Acoustics, Signal Processing, and Related Topics [SIP, EA, SP]/ Medical Image Engineering, Analysis, Recognition, etc. [MI] 
Paper Information
Registration To SIP 
Conference Code 2018-03-SIP-EA-SP-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Accuracy Improvement of Fashon Style Classification by Appropriate Training Data and Estimation of Human Regions 
Sub Title (in English)  
Keyword(1) Fashion style estimation  
Keyword(2) large-scale data set  
Keyword(3) deep neural network  
Keyword(4) semantic segmentation  
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1st Author's Name Takeshi Nakajima  
1st Author's Affiliation Meiji University (Meiji Univ.)
2nd Author's Name Takuro Oki  
2nd Author's Affiliation Meiji University (Meiji Univ.)
3rd Author's Name Ryusuke Miyamoto  
3rd Author's Affiliation Meiji University (Meiji Univ.)
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Speaker Author-1 
Date Time 2018-03-19 15:35:00 
Presentation Time 25 minutes 
Registration for SIP 
Paper # EA2017-137, SIP2017-146, SP2017-120 
Volume (vol) vol.117 
Number (no) no.515(EA), no.516(SIP), no.517(SP) 
Page pp.197-202 
#Pages
Date of Issue 2018-03-12 (EA, SIP, SP) 


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