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| Presentation | 2017-02-20 10:30 A parallel computation method of super resolution using convolutional neural networks Yusuke Sugawara, Sayaka Shiota, Hitoshi Kiya (Tokyo Metro. Univ.)  ITS2016-44 IE2016-102 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | An acceleration method for interpolation-based super resolution methods using convolutional neural networks, represented by SRCNN and VDSR is proposed in this article. In the proposed method, estimated pixels are classified into some types and then high resolution images are directly generated from low resolution ones by using optimized convolutional neural networks for each type. It allows us to adapt smaller filter sizes to convolutional neural networks than conventional ones, so that the computational complexity can be reduced. A number of experiments are carried out to demonstrate that the proposed method can be applied to various interpolation-based super resolution methods using convolutional neural networks. The effectiveness of the proposed method for multiple upscale factors is also confirmed. In addition, the proposed method outperforms conventional ones in terms of the quality of estimated images under some conditions. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Super Resolution / Convolutional Neural Network / Parallel Computation / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 116, no. 464, IE2016-102, pp. 13-18, Feb. 2017. | |
| Paper # | IE2016-102 | |
| Date of Issue | 2017-02-13 (ITS, IE) | |
| 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 | ITS2016-44 IE2016-102 |
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| Conference Information | |
| Committee | IE ITS ITE-AIT ITE-HI ITE-ME ITE-MMS ITE-CE |
| Conference Date | 2017-02-20 - 2017-02-21 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Hokkaido Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Image Processing, etc. |
| Paper Information | |
| Registration To | IE |
| Conference Code | 2017-02-IE-ITS-AIT-HI-ME-MMS-CE |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A parallel computation method of super resolution using convolutional neural networks |
| Sub Title (in English) | |
| Keyword(1) | Super Resolution |
| Keyword(2) | Convolutional Neural Network |
| Keyword(3) | Parallel Computation |
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| 1st Author's Name | Yusuke Sugawara |
| 1st Author's Affiliation | Tokyo Metro. Univ. (Tokyo Metro. Univ.) |
| 2nd Author's Name | Sayaka Shiota |
| 2nd Author's Affiliation | Tokyo Metro. Univ. (Tokyo Metro. Univ.) |
| 3rd Author's Name | Hitoshi Kiya |
| 3rd Author's Affiliation | Tokyo Metro. Univ. (Tokyo Metro. Univ.) |
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| Speaker | Author-1 |
| Date Time | 2017-02-20 10:30:00 |
| Presentation Time | 15 minutes |
| Registration for | IE |
| Paper # | ITS2016-44, IE2016-102 |
| Volume (vol) | vol.116 |
| Number (no) | no.463(ITS), no.464(IE) |
| Page | pp.13-18 |
| #Pages | 6 |
| Date of Issue | 2017-02-13 (ITS, IE) |
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