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Paper Abstract and Keywords
Presentation 2020-12-01 14:25
Interpretability of deep neural networks with self-organizing map modules.
Takahiro Sono, Keiichi Horio (KIT) SIS2020-32
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, the technology of neural networks has made great progress due to the improvement of computational power.As one of the features of these networks, more complex networks have been constructed, and many of the discrimination results are beyond human understanding.This makes it difficult to understand process in neural networks when we want to evaluate the clusters formed by human judgment, because there is no data to supervise the clusters, although we want to adapt them as classification problems.In this study, we constructed a full-layer visualization model using a neural network with self-organizing maps as a unit, and tested its interpretability.
Keyword (in Japanese) (See Japanese page) 
(in English) shape classification / neural network / self-organizing map / clustering / interpretability / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 269, SIS2020-32, pp. 27-30, Dec. 2020.
Paper # SIS2020-32 
Date of Issue 2020-11-24 (SIS) 
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 SIS2020-32

Conference Information
Committee SIS  
Conference Date 2020-12-01 - 2020-12-01 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Smart Personal Systems, etc. 
Paper Information
Registration To SIS 
Conference Code 2020-12-SIS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Interpretability of deep neural networks with self-organizing map modules. 
Sub Title (in English)  
Keyword(1) shape classification  
Keyword(2) neural network  
Keyword(3) self-organizing map  
Keyword(4) clustering  
Keyword(5) interpretability  
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1st Author's Name Takahiro Sono  
1st Author's Affiliation Kyushu Institute of Technology (KIT)
2nd Author's Name Keiichi Horio  
2nd Author's Affiliation Kyushu Institute of Technology (KIT)
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Speaker Author-1 
Date Time 2020-12-01 14:25:00 
Presentation Time 25 minutes 
Registration for SIS 
Paper # SIS2020-32 
Volume (vol) vol.120 
Number (no) no.269 
Page pp.27-30 
#Pages 4 
Date of Issue 2020-11-24 (SIS) 

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