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Paper Abstract and Keywords
Presentation 2018-12-13 10:30
Candidate Reduction Method Using Hierarchical Overlapping Clustering and Convolutional Neural Network for Fast Chinese Character Recognition
Soichi Tashima, Hideaki Goto (Tohoku Univ.) PRMU2018-77
Abstract (in Japanese) (See Japanese page) 
(in English) Along with the widespread of the mobile devices equipped with cameras, many applications using the camera function have appeared and the demands for optical character recognition is growing. Although the nearest neighbor search based on the linear search with feature vectors can be easily implemented, its problem is that the computational cost increases linearly by the dimensionality of feature vectors and the number of classes. It is necessary to reduce the computational cost in handwritten character recognition, especially in case of Chinese characters that have complex structures and consist of thousands of classes, on such devices with limited performance. In this paper, we discuss the parameter settings for the candidate reduction system based on the hierarchical overlapping clustering and CNN-based feature extractor. The experimental results show that CNN-based feature extractor enables the system to reduce more candidates and contributes to 2.56 times faster recognition with 0.51% accuracy drop compared with our former method.
Keyword (in Japanese) (See Japanese page) 
(in English) Optical Character Recognition / Handwritten Chinese Character Recognition / Hierarchical Overlapping Clustering / Convolutional Neural Network / Nearest Neighbor Search / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 362, PRMU2018-77, pp. 13-18, Dec. 2018.
Paper # PRMU2018-77 
Date of Issue 2018-12-06 (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 PRMU2018-77

Conference Information
Committee PRMU  
Conference Date 2018-12-13 - 2018-12-14 
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 2018-12-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Candidate Reduction Method Using Hierarchical Overlapping Clustering and Convolutional Neural Network for Fast Chinese Character Recognition 
Sub Title (in English)  
Keyword(1) Optical Character Recognition  
Keyword(2) Handwritten Chinese Character Recognition  
Keyword(3) Hierarchical Overlapping Clustering  
Keyword(4) Convolutional Neural Network  
Keyword(5) Nearest Neighbor Search  
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Keyword(7)  
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1st Author's Name Soichi Tashima  
1st Author's Affiliation Tohoku University (Tohoku Univ.)
2nd Author's Name Hideaki Goto  
2nd Author's Affiliation Tohoku University (Tohoku Univ.)
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Speaker Author-1 
Date Time 2018-12-13 10:30:00 
Presentation Time 15 minutes 
Registration for PRMU 
Paper # PRMU2018-77 
Volume (vol) vol.118 
Number (no) no.362 
Page pp.13-18 
#Pages 6 
Date of Issue 2018-12-06 (PRMU) 

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