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| 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 |
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| 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. |
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| 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 | |
| Copyright and 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 | MoNA2017-55 |
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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 |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 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 | 1 |
| Date Time | 2018-01-19 13:55:00 |
| Presentation Time | 25 |
| Registration for | MoNA |
| Paper # | MoNA2017-55 |
| Volume (vol) | 117 |
| Number (no) | no.390 |
| Page | pp.79-82 |
| #Pages | 4 |
| Date of Issue | 2018-01-11 (MoNA) |
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