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Paper Abstract and Keywords
Presentation 2018-01-19 13:55
Automatic biometric data generation by Generative Adversarial Network and its application to deep learning sample
Tatsuya Takahata (Tokyo University of Technology), Kazumasa Horie (University of Tsukuba), Yuri Akizuki (Kumamoto Univ.), Soichiro Ikuno (Tokyo University of Technology) MoNA2017-55
Abstract (in Japanese) (See Japanese page) 
(in English) While deep learning has high learning performance and recognition performance, it requires a large amount of sample data for learning. However, it takes time to collect daily personal biological data such as body temperature. Therefore, it is difficult to adopt the biological data as learning data of the deep learning at the early stage of collection.

In the present study, the virtual learning data for the deep learning are generated by Generative Adversarial Network (GAN) using data at the early stage of collection. Additionally, the generated data are adopted for learning data of the deep learning.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep Learning / GAN / Data Analysis / Biological Data / Automatically Generated / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 390, MoNA2017-55, pp. 79-82, Jan. 2018.
Paper # MoNA2017-55 
Date of Issue 2018-01-11 (MoNA) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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)
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Conference Information
Committee MoNA  
Conference Date 2018-01-18 - 2018-01-19 
Place (in Japanese) (See Japanese page) 
Place (in English) Campus Plaza Kyoto 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Mobile Network, Application of Machine Learning, Mobile Data, etc. 
Paper Information
Registration To MoNA 
Conference Code 2018-01-MoNA 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automatic biometric data generation by Generative Adversarial Network and its application to deep learning sample 
Sub Title (in English)  
Keyword(1) Deep Learning  
Keyword(2) GAN  
Keyword(3) Data Analysis  
Keyword(4) Biological Data  
Keyword(5) Automatically Generated  
1st Author's Name Tatsuya Takahata  
1st Author's Affiliation Tokyo University of Technology (Tokyo University of Technology)
2nd Author's Name Kazumasa Horie  
2nd Author's Affiliation University of Tsukuba (University of Tsukuba)
3rd Author's Name Yuri Akizuki  
3rd Author's Affiliation Kumamoto University (Kumamoto Univ.)
4th Author's Name Soichiro Ikuno  
4th Author's Affiliation Tokyo University of Technology (Tokyo University of Technology)
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Speaker Author-1 
Date Time 2018-01-19 13:55:00 
Presentation Time 25 minutes 
Registration for MoNA 
Paper # MoNA2017-55 
Volume (vol) vol.117 
Number (no) no.390 
Page pp.79-82 
Date of Issue 2018-01-11 (MoNA) 

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