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Paper Abstract and Keywords
Presentation 2018-03-20 09:00
[Poster Presentation] Image Super-Resolution via Convolutional Neural Network Using An Orthogonal Projection Layer
Nobuyuki Baba, Hidetomo Kataoka, Daichi Kitahara, Akira Hirabayashi (Ritsumeikan Univ.) EA2017-165 SIP2017-174 SP2017-148
Abstract (in Japanese) (See Japanese page) 
(in English) We propose a super-resolution method using a convolutional neural network (CNN) that reduces obser- vation error during training and exploits an orthogonal projection layer after training. A conventional super-resolu- tion method using CNN suffers from black or white artifact. To solve this problem, we add an observation error to the cost function for training. This guarantees consistency for training examples, but not for a novel input data after training. Hence, we further introduce the orthogonal projection onto a linear manifold, in which the observation error is completely zero. These two ideas enable us to produce high quality super-resolution results without the artifact. Simulation results show the effectiveness of the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) Super-resolution / convolutional neural network / orthigonarl projection layer / / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 516, SIP2017-174, pp. 347-352, March 2018.
Paper # SIP2017-174 
Date of Issue 2018-03-12 (EA, SIP, SP) 
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 EA2017-165 SIP2017-174 SP2017-148

Conference Information
Committee SIP EA SP MI  
Conference Date 2018-03-19 - 2018-03-20 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech, Engineering/Electro Acoustics, Signal Processing, and Related Topics [SIP, EA, SP]/ Medical Image Engineering, Analysis, Recognition, etc. [MI] 
Paper Information
Registration To SIP 
Conference Code 2018-03-SIP-EA-SP-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Image Super-Resolution via Convolutional Neural Network Using An Orthogonal Projection Layer 
Sub Title (in English)  
Keyword(1) Super-resolution  
Keyword(2) convolutional neural network  
Keyword(3) orthigonarl projection layer  
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1st Author's Name Nobuyuki Baba  
1st Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
2nd Author's Name Hidetomo Kataoka  
2nd Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
3rd Author's Name Daichi Kitahara  
3rd Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
4th Author's Name Akira Hirabayashi  
4th Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
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Speaker Author-1 
Date Time 2018-03-20 09:00:00 
Presentation Time 90 minutes 
Registration for SIP 
Paper # EA2017-165, SIP2017-174, SP2017-148 
Volume (vol) vol.117 
Number (no) no.515(EA), no.516(SIP), no.517(SP) 
Page pp.347-352 
#Pages
Date of Issue 2018-03-12 (EA, SIP, SP) 


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