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Paper Abstract and Keywords
Presentation 2020-05-29 14:30
A method for analyze causes of deterioration of predict quality when Deep Learning is applied to instance segmentation
Tomonori Kubota, Takanori Nakao, Masafumi Katoh, Eiji Yoshida, Hidenobu Miyoshi (Fujitsu Lab.) SIP2020-14 BioX2020-14 IE2020-14 MI2020-14
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose a method to analyze the cause of deterioration of prediction accuracy in instance segmentation by deep learning. We have proposed a method to analyze the cause of deterioration of prediction accuracy in object recognition and object detection. This method is extended to instance segmentation (Mask Scoring R-CNN). This method extracts and visualizes the cause at the pixel grain size in the image (input image) in which the quality of the prediction result deteriorates. And, by applying the cause information of the pixel grain size extracted by this technique to the input image, it can be corrected to the image with improved prediction accuracy. That is, it can be shown that the cause information extracted by this method correctly represents the cause.
Keyword (in Japanese) (See Japanese page) 
(in English) deep learning / convolutional neural network / video analysis / segmentation / XAI / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 39, IE2020-14, pp. 67-72, May 2020.
Paper # IE2020-14 
Date of Issue 2020-05-21 (SIP, BioX, IE, MI) 
ISSN Online edition: ISSN 2432-6380
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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 SIP2020-14 BioX2020-14 IE2020-14 MI2020-14

Conference Information
Committee MI IE SIP BioX ITE-IST ITE-ME  
Conference Date 2020-05-28 - 2020-05-29 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image and signal processing/analysis/AI technology, and their application 
Paper Information
Registration To IE 
Conference Code 2020-05-MI-IE-SIP-BioX-IST-ME 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A method for analyze causes of deterioration of predict quality when Deep Learning is applied to instance segmentation 
Sub Title (in English)  
Keyword(1) deep learning  
Keyword(2) convolutional neural network  
Keyword(3) video analysis  
Keyword(4) segmentation  
Keyword(5) XAI  
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1st Author's Name Tomonori Kubota  
1st Author's Affiliation Fujitsu Laboratories LTD. (Fujitsu Lab.)
2nd Author's Name Takanori Nakao  
2nd Author's Affiliation Fujitsu Laboratories LTD. (Fujitsu Lab.)
3rd Author's Name Masafumi Katoh  
3rd Author's Affiliation Fujitsu Laboratories LTD. (Fujitsu Lab.)
4th Author's Name Eiji Yoshida  
4th Author's Affiliation Fujitsu Laboratories LTD. (Fujitsu Lab.)
5th Author's Name Hidenobu Miyoshi  
5th Author's Affiliation Fujitsu Laboratories LTD. (Fujitsu Lab.)
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Speaker Author-1 
Date Time 2020-05-29 14:30:00 
Presentation Time 20 minutes 
Registration for IE 
Paper # SIP2020-14, BioX2020-14, IE2020-14, MI2020-14 
Volume (vol) vol.120 
Number (no) no.38(SIP), no.37(BioX), no.39(IE), no.40(MI) 
Page pp.67-72 
#Pages
Date of Issue 2020-05-21 (SIP, BioX, IE, MI) 


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