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Paper Abstract and Keywords
Presentation 2019-03-13 15:15
[Poster Presentation] Human Touch Character Font System -- Generation of hand written HIRAGANA using Neural Network --
Yuto Yamamoto, Michiharu Niimi (KIT) EMM2018-106
Abstract (in Japanese) (See Japanese page) 
(in English) For modern computer society, one may need human touch character font system to enjoy making communication through Internet. An approach to build such font system is to modify the usual font installed in one's computer devices. For this approach, we report hand written HIRAGANA character generation using neural network. As neural network in this paper, a simple auto encoder consisting of input layer, middle layer and output layer, and deep neural network based on GAN (Generative Adversarial Netowrk) called zi2zi are adopted. We use these neural networks as an image modification filter that input data is usual font data and output data is hand written character. We investigate the feasibility of those neural networks to generate hand written characters of HIRAGANA experimentally. For auto encoder, the output image was like rounded character of input rasterized font, and it was not like hand written characters of training data. On the other hand, for zi2zi, we confirmed that the output image is quite like hand written character if we can prepare much training data. However, for untrained data, the output image is almost like hand written character only in some case. In most cases, the output image is roughly equal to a character or was not able to be recognized as a character visually.
Keyword (in Japanese) (See Japanese page) 
(in English) Auto Encoder / GAN / hand written character font / machine learning / font generation / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 494, EMM2018-106, pp. 77-82, March 2019.
Paper # EMM2018-106 
Date of Issue 2019-03-06 (EMM) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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)
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Conference Information
Committee EMM  
Conference Date 2019-03-13 - 2019-03-14 
Place (in Japanese) (See Japanese page) 
Place (in English) TBD 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image and Sound Quality, Metrics for Perception and Recognition, Human Auditory and Visual System, etc. 
Paper Information
Registration To EMM 
Conference Code 2019-03-EMM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Human Touch Character Font System 
Sub Title (in English) Generation of hand written HIRAGANA using Neural Network 
Keyword(1) Auto Encoder  
Keyword(2) GAN  
Keyword(3) hand written character font  
Keyword(4) machine learning  
Keyword(5) font generation  
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1st Author's Name Yuto Yamamoto  
1st Author's Affiliation Kyushu Institute of Technology (KIT)
2nd Author's Name Michiharu Niimi  
2nd Author's Affiliation Kyushu Institute of Technology (KIT)
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Speaker Author-1 
Date Time 2019-03-13 15:15:00 
Presentation Time 60 minutes 
Registration for EMM 
Paper # EMM2018-106 
Volume (vol) vol.118 
Number (no) no.494 
Page pp.77-82 
#Pages
Date of Issue 2019-03-06 (EMM) 


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