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Paper Abstract and Keywords
Presentation 2019-02-14 14:40
Crater Detection Robust to Degradation and Illumination Changes Using Convolutional Neural Network
Takayuki Ishida (JAXA), Masaki Takahashi (Keio Univ.), Seisuke Fukuda (JAXA) SANE2018-125
Abstract (in Japanese) (See Japanese page) 
(in English) Recent planetary exploration requires high precision landing technology, and one of the its solution is optical navigation which collates taken images and maps generated in advance. Especially craters are distributed over whole lunar surface, crater-based navigation is better way to navigate probes on the moon. Problems when detecting craters from taken images are apparent changes due to illumination condition and shape changes due to degradation. In this paper, a new crater detection method that combines linear classifier and convolutional neural network is proposed. Simulation results show our method is robust to changes of illumination and shape of craters.
Keyword (in Japanese) (See Japanese page) 
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Reference Info. IEICE Tech. Rep., vol. 118, no. 441, SANE2018-125, pp. 83-88, Feb. 2019.
Paper # SANE2018-125 
Date of Issue 2019-02-06 (SANE) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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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Conference Information
Committee SANE SAT  
Conference Date 2019-02-13 - 2019-02-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Tanegashima Island 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Satellite Application and General 
Paper Information
Registration To SANE 
Conference Code 2019-02-SANE-SAT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Crater Detection Robust to Degradation and Illumination Changes Using Convolutional Neural Network 
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1st Author's Name Takayuki Ishida  
1st Author's Affiliation Japan Aerospace Exploration Agency (JAXA)
2nd Author's Name Masaki Takahashi  
2nd Author's Affiliation Keio University (Keio Univ.)
3rd Author's Name Seisuke Fukuda  
3rd Author's Affiliation Japan Aerospace Exploration Agency (JAXA)
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Date Time 2019-02-14 14:40:00 
Presentation Time 25 minutes 
Registration for SANE 
Paper # SANE2018-125 
Volume (vol) vol.118 
Number (no) no.441 
Page pp.83-88 
#Pages
Date of Issue 2019-02-06 (SANE) 


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