Paper Abstract and Keywords |
Presentation |
2017-10-05 14:20
Unsupervised Adaptive PolSAR Land Classification System Using Quaternion Neural Networks Hyunsoo Kim, Akira Hirose (Univ. of Tokyo) SANE2017-57 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
We propose an unsupervised adaptive PolSAR land classification system using quaternion neural networks. Most of the existing PolSAR land classification systems use a set of feature information that humans designed beforehand. However, such methods will face limitations in the near future when we expect classification into a large number of land categories recognizable to humans. By using quaternion auto-encoder, our proposed system extracts feature information based on the natural distribution of PolSAR features. Then, we show that the extracted features are classified by the quaternion SOM in an unsupervised manner. As a result, we can discover even new and more detailed land categories. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
polarimetric synthetic aperture radar (PolSAR) / unsupervised land classification / quaternion neural network / Poincare parameter / auto-encoder / self-organizing map (SOM) / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 222, SANE2017-57, pp. 73-78, Oct. 2017. |
Paper # |
SANE2017-57 |
Date of Issue |
2017-09-27 (SANE) |
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) |
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SANE2017-57 |
Conference Information |
Committee |
SANE |
Conference Date |
2017-10-04 - 2017-10-05 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Maison franco - japonaise (Tokyo) |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
The 14th workshop on subsurface electromagnetic measurement |
Paper Information |
Registration To |
SANE |
Conference Code |
2017-10-SANE |
Language |
English (Japanese title is available) |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Unsupervised Adaptive PolSAR Land Classification System Using Quaternion Neural Networks |
Sub Title (in English) |
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Keyword(1) |
polarimetric synthetic aperture radar (PolSAR) |
Keyword(2) |
unsupervised land classification |
Keyword(3) |
quaternion neural network |
Keyword(4) |
Poincare parameter |
Keyword(5) |
auto-encoder |
Keyword(6) |
self-organizing map (SOM) |
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1st Author's Name |
Hyunsoo Kim |
1st Author's Affiliation |
The University of Tokyo (Univ. of Tokyo) |
2nd Author's Name |
Akira Hirose |
2nd Author's Affiliation |
The University of Tokyo (Univ. of Tokyo) |
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Speaker |
Author-1 |
Date Time |
2017-10-05 14:20:00 |
Presentation Time |
25 minutes |
Registration for |
SANE |
Paper # |
SANE2017-57 |
Volume (vol) |
vol.117 |
Number (no) |
no.222 |
Page |
pp.73-78 |
#Pages |
6 |
Date of Issue |
2017-09-27 (SANE) |