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| Presentation | 2021-03-05 09:55 Aspect classification by using complex-valued reservoir computing Bungo Konishi, Akira Hirose, Ryo Natsuaki (UT)  NC2020-65 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Synthetic aperture radar (SAR) is widely used for ground surface classification because of their information on vegetation and soil that are unavailable in optical data. Generally, image segmentation employs convolutional neural networks (CNNs). However, they have serious problems such as a long learning time and resolution degradation in segmentation results in their convolution and pooling process. In this paper, we propose complex-valued reservoir computing (CVRC) to deal with complex-valued image in interferometric SAR (InSAR). We segment and classify InSAR image data by using CVRC successfully with a low computational cost and a high resolution. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | reservoir computing / complex-valued neural network / interferometric synthetic aperture radar / aspect classification / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 403, NC2020-65, pp. 127-132, March 2021. | |
| Paper # | NC2020-65 | |
| Date of Issue | 2021-02-24 (NC) | |
| ISSN | 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 | NC2020-65 |
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| Conference Information | |
| Committee | NC MBE |
| Conference Date | 2021-03-03 - 2021-03-05 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Neuro Computing, Medical Engineering, etc. |
| Paper Information | |
| Registration To | NC |
| Conference Code | 2021-03-NC-MBE |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Aspect classification by using complex-valued reservoir computing |
| Sub Title (in English) | |
| Keyword(1) | reservoir computing |
| Keyword(2) | complex-valued neural network |
| Keyword(3) | interferometric synthetic aperture radar |
| Keyword(4) | aspect classification |
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| 1st Author's Name | Bungo Konishi |
| 1st Author's Affiliation | The University of Tokyo (UT) |
| 2nd Author's Name | Akira Hirose |
| 2nd Author's Affiliation | The University of Tokyo (UT) |
| 3rd Author's Name | Ryo Natsuaki |
| 3rd Author's Affiliation | The University of Tokyo (UT) |
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| Speaker | Author-1 |
| Date Time | 2021-03-05 09:55:00 |
| Presentation Time | 25 minutes |
| Registration for | NC |
| Paper # | NC2020-65 |
| Volume (vol) | vol.120 |
| Number (no) | no.403 |
| Page | pp.127-132 |
| #Pages | 6 |
| Date of Issue | 2021-02-24 (NC) |
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