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Paper Abstract and Keywords
Presentation 2016-12-15 14:30
[Invited Talk] Dynamic datasets for flexible pattern recognition -- The 2nd Grand Challenge of PRMU --
Mitsuru Ambai (Denso IT Laboratory, Inc.) PRMU2016-113
Abstract (in Japanese) (See Japanese page) 
(in English) Standard pattern recognition uses N labelled data to learn a mapping function that relates an input pattern to a pre-defined label. Deep learning made great progress on improving performances of such standard pattern recognition tasks including multi-class classification, segmentation and object detection, etc. Software libraries of deep learning have now been widely used by not only researchers but engineers who are not familiar with machine learning. Can any problems of pattern recognition be solved if we collect a sufficient number of labelled data? If we had them, it might be true. Unfortunately, it is impossible to collect labelled data for particular types of pattern recognition tasks, e.g. inferring control signals of a robot arm from an image sequence. In such the case, we believe that the most promising approach is to learn the inferring function by interacting with a virtual environment. While we should call conventional dataset such as MNIST and ImageNet as static dataset, we should call the virtual enviroment as dynamic dataset. This talk discusses flexible pattern recognition that learns from the dynamic dataset to deal with difficulty of labelled data collection.
Keyword (in Japanese) (See Japanese page) 
(in English) grand challenge / dataset / / / / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 366, PRMU2016-113, pp. 11-11, Dec. 2016.
Paper # PRMU2016-113 
Date of Issue 2016-12-08 (PRMU) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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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 PRMU2016-113

Conference Information
Committee PRMU  
Conference Date 2016-12-15 - 2016-12-16 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To PRMU 
Conference Code 2016-12-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Dynamic datasets for flexible pattern recognition 
Sub Title (in English) The 2nd Grand Challenge of PRMU 
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Keyword(2) dataset  
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1st Author's Name Mitsuru Ambai  
1st Author's Affiliation Denso IT Laboratory, Inc. (Denso IT Laboratory, Inc.)
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Speaker Author-1 
Date Time 2016-12-15 14:30:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2016-113 
Volume (vol) vol.116 
Number (no) no.366 
Page p.11 
#Pages 1 
Date of Issue 2016-12-08 (PRMU) 

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