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Paper Abstract and Keywords
Presentation 2022-05-20 16:20
Visualization of Important Features for Classifier Decisions using Deep Image Synthesis
Yushi Haku, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) SIP2022-28 BioX2022-28 IE2022-28 MI2022-28
Abstract (in Japanese) (See Japanese page) 
(in English) It is difficult to know the basis for the decisions of machine learning models, and it is necessary to provide a highly interpretable explanation for the model's predictions. In this study, we developed a framework for visualizing features related to the decisions of classification models based on deep image generation. Similar and adversary images are generated from the input images, and the differences between them are visualized. Conditional Variational AutoEncoder was used for image generation, aiming at image transformation considering data distribution in the feature space. The effectiveness of the proposed method was confirmed on the MNIST dataset used for handwritten character recognition, and important features in the classification of the number of fibula fragments were visualized using mandible reconstruction planning data.
Keyword (in Japanese) (See Japanese page) 
(in English) Interpretability / Classifier / Deep image generarion / Mandibular reconstruction / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 31, MI2022-28, pp. 144-149, May 2022.
Paper # MI2022-28 
Date of Issue 2022-05-12 (SIP, BioX, IE, MI) 
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 SIP2022-28 BioX2022-28 IE2022-28 MI2022-28

Conference Information
Committee SIP BioX IE MI ITE-IST ITE-ME  
Conference Date 2022-05-19 - 2022-05-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Kumamoto University Kurokami Campus 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MI 
Conference Code 2022-05-SIP-BioX-IE-MI-IST-ME 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Visualization of Important Features for Classifier Decisions using Deep Image Synthesis 
Sub Title (in English)  
Keyword(1) Interpretability  
Keyword(2) Classifier  
Keyword(3) Deep image generarion  
Keyword(4) Mandibular reconstruction  
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1st Author's Name Yushi Haku  
1st Author's Affiliation Kyoto University (Kyoto Univ.)
2nd Author's Name Megumi Nakao  
2nd Author's Affiliation Kyoto University (Kyoto Univ.)
3rd Author's Name Tetsuya Matsuda  
3rd Author's Affiliation Kyoto University (Kyoto Univ.)
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Speaker Author-1 
Date Time 2022-05-20 16:20:00 
Presentation Time 20 minutes 
Registration for MI 
Paper # SIP2022-28, BioX2022-28, IE2022-28, MI2022-28 
Volume (vol) vol.122 
Number (no) no.28(SIP), no.29(BioX), no.30(IE), no.31(MI) 
Page pp.144-149 
#Pages 6 
Date of Issue 2022-05-12 (SIP, BioX, IE, MI) 

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