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| Presentation | 2019-11-01 10:20 Study on Land Use Classification of PolSAR Data by Using Convolutional Neural Network Nanako Saito, Masanori Gocho, Hiroyoshi Yamada, Ryoichi Sato, Yoshio Yamaguchi (Niigata Univ.)  SANE2019-63 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Polarimetric Synthetic Aperture Radar (PolSAR) has been attracting attention in ground target detection and classification. This is because it can observe wide area regardless of time zone and weather, and analyze in detail by using polarimetric information. Various methods, such as model-based scattering power decomposition, eigenvalue analysis and so forth, have been proposed for the analysis of PolSAR data. Recently, classification techniques by using machine learning have been intensively studied to reduce misclassification and improve classification accuracy. In this paper, we present some experimental results of land use classification of ALOS-2/PALSAR-2 data by using convolutional neural network (CNN), and compare classification performance with the case of scattering power decomposition and support vector machine (SVM). | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Polarimetric Synthetic Aperture Radar (PolSAR) / ALOS-2 / Convolutional neural network / Support vector machine / Land use map / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 255, SANE2019-63, pp. 77-82, Oct. 2019. | |
| Paper # | SANE2019-63 | |
| Date of Issue | 2019-10-24 (SANE) | |
| 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 | SANE2019-63 |
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| Conference Information | |
| Committee | SANE |
| Conference Date | 2019-10-31 - 2019-11-01 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | KOREA (Jeju) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | ICSANE2019 |
| Paper Information | |
| Registration To | SANE |
| Conference Code | 2019-10-SANE |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Study on Land Use Classification of PolSAR Data by Using Convolutional Neural Network |
| Sub Title (in English) | |
| Keyword(1) | Polarimetric Synthetic Aperture Radar (PolSAR) |
| Keyword(2) | ALOS-2 |
| Keyword(3) | Convolutional neural network |
| Keyword(4) | Support vector machine |
| Keyword(5) | Land use map |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Nanako Saito |
| 1st Author's Affiliation | Niigata University (Niigata Univ.) |
| 2nd Author's Name | Masanori Gocho |
| 2nd Author's Affiliation | Niigata University (Niigata Univ.) |
| 3rd Author's Name | Hiroyoshi Yamada |
| 3rd Author's Affiliation | Niigata University (Niigata Univ.) |
| 4th Author's Name | Ryoichi Sato |
| 4th Author's Affiliation | Niigata University (Niigata Univ.) |
| 5th Author's Name | Yoshio Yamaguchi |
| 5th Author's Affiliation | Niigata University (Niigata Univ.) |
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| Speaker | Author-1 |
| Date Time | 2019-11-01 10:20:00 |
| Presentation Time | 20 minutes |
| Registration for | SANE |
| Paper # | SANE2019-63 |
| Volume (vol) | vol.119 |
| Number (no) | no.255 |
| Page | pp.77-82 |
| #Pages | 6 |
| Date of Issue | 2019-10-24 (SANE) |
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