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Paper Abstract and Keywords
Presentation 2020-12-18 17:00
An evaluation method of area detection AI based on contribution pattern variation with noise addition
Yasuhide Mori, Naofumi Hama, Masashi Egi (Hitachi) PRMU2020-67
Abstract (in Japanese) (See Japanese page) 
(in English) The processing of image recognition AI using machine learning is generally black-boxed, and grasping the operating characteristics is an issue. In the classification AI, a method of calculating the contribution of each place in the image to the output result is widely used as a method of XAI (eXplainable AI). On the other hand, in the region extraction AI, the contribution of each place in the image to the output cannot be calculated simply like the classification AI. In this report, we develop a procedure to calculate the degree of contribution to the region extraction AI, and propose an AI characteristic evaluation procedure by observing how the pattern of the degree of contribution changes due to added noise. As a result of the experiment, it was suggested that the region extraction AI operation characteristics could be grasped.
Keyword (in Japanese) (See Japanese page) 
(in English) AI / XAI / explainable AI / image recognition / image classification / region extraction / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 300, PRMU2020-67, pp. 166-171, Dec. 2020.
Paper # PRMU2020-67 
Date of Issue 2020-12-10 (PRMU) 
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 PRMU2020-67

Conference Information
Committee PRMU  
Conference Date 2020-12-17 - 2020-12-18 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Transfer learning and few shot learning 
Paper Information
Registration To PRMU 
Conference Code 2020-12-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An evaluation method of area detection AI based on contribution pattern variation with noise addition 
Sub Title (in English)  
Keyword(1) AI  
Keyword(2) XAI  
Keyword(3) explainable AI  
Keyword(4) image recognition  
Keyword(5) image classification  
Keyword(6) region extraction  
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Keyword(8)  
1st Author's Name Yasuhide Mori  
1st Author's Affiliation Hitachi, Ltd. (Hitachi)
2nd Author's Name Naofumi Hama  
2nd Author's Affiliation Hitachi, Ltd. (Hitachi)
3rd Author's Name Masashi Egi  
3rd Author's Affiliation Hitachi, Ltd. (Hitachi)
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Speaker Author-1 
Date Time 2020-12-18 17:00:00 
Presentation Time 15 minutes 
Registration for PRMU 
Paper # PRMU2020-67 
Volume (vol) vol.120 
Number (no) no.300 
Page pp.166-171 
#Pages 6 
Date of Issue 2020-12-10 (PRMU) 

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