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Paper Abstract and Keywords
Presentation 2020-03-17 09:30
Object area extraction with biased training data set
Ryo Nakamura, Yoshiaki Ueda, Jun Fujiki, Masaru Tanaka (Fukuoka Univ) PRMU2019-88
Abstract (in Japanese) (See Japanese page) 
(in English) In order to extract an object region using machine learning, it is necessary to give a teacher label to each pixel. Providing a teacher label for each pixel is a very laborious task. In this paper, we propose a method to extract an area of an unidentified object without labeling every pixel by identifying the unidentified object with high precision. In this method, the training image set is not input as it is, but plural small patches are extracted from the training image set, and the discriminator is learned by using them as input. The learned discriminator extracts an object region by obtaining a discrimination ratio by using raster scan for an image to be extracted. At that time, though it is necessary to discriminate the non-discrimination object with high precision, by using the asymmetry of the training image set, the discrimination bias is utilized, and by discriminating the non-discrimination object with high precision, the region extraction of the discrimination object is carried out. And, visualization is carried out by making the identification ratio to be an image of αch.
Keyword (in Japanese) (See Japanese page) 
(in English) BTD / Object area extraction / / / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 481, PRMU2019-88, pp. 115-119, March 2020.
Paper # PRMU2019-88 
Date of Issue 2020-03-09 (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 PRMU2019-88

Conference Information
Committee PRMU IPSJ-CVIM  
Conference Date 2020-03-16 - 2020-03-17 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2020-03-PRMU-CVIM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Object area extraction with biased training data set 
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Keyword(1) BTD  
Keyword(2) Object area extraction  
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1st Author's Name Ryo Nakamura  
1st Author's Affiliation Fukuoka University (Fukuoka Univ)
2nd Author's Name Yoshiaki Ueda  
2nd Author's Affiliation Fukuoka University (Fukuoka Univ)
3rd Author's Name Jun Fujiki  
3rd Author's Affiliation Fukuoka University (Fukuoka Univ)
4th Author's Name Masaru Tanaka  
4th Author's Affiliation Fukuoka University (Fukuoka Univ)
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Speaker Author-1 
Date Time 2020-03-17 09:30:00 
Presentation Time 15 minutes 
Registration for PRMU 
Paper # PRMU2019-88 
Volume (vol) vol.119 
Number (no) no.481 
Page pp.115-119 
#Pages 5 
Date of Issue 2020-03-09 (PRMU) 

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