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Paper Abstract and Keywords
Presentation 2016-02-21 09:30
Fish Image Recognition using Convolutional Neural Network
Kentaro Wakisaka, Takeshi Saitoh (kyutech) PRMU2015-132 CNR2015-33
Abstract (in Japanese) (See Japanese page) 
(in English) We are studying on development of image-based fish identification system. Most traditional researches use the geometric features or texture features designed by manual design. And to extract correct fish region and calculate features, traditional researches require several restrictions, such as take a fish image with a white or uniform background, give several feature points by manual operation. To solve these problems, this paper proposes a fish image recognition method using convolutional neural network which attracts attention in recent years. Three methods based on CNN are applied to our image data set contained 129 fish species. As a result, the method to extract the features from an intermediate layer in CNN which learned by fine-tuning and classify by SVM obtained the highest recognition accuracy. Furthermore, it is found that this accuracy is same as hand-craft approach of our previous study.
Keyword (in Japanese) (See Japanese page) 
(in English) Convolutional neural network / SVM / fish image / Caffenet / / / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 456, PRMU2015-132, pp. 1-5, Feb. 2016.
Paper # PRMU2015-132 
Date of Issue 2016-02-14 (PRMU, CNR) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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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 PRMU2015-132 CNR2015-33

Conference Information
Committee PRMU CNR  
Conference Date 2016-02-21 - 2016-02-22 
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 2016-02-PRMU-CNR 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Fish Image Recognition using Convolutional Neural Network 
Sub Title (in English)  
Keyword(1) Convolutional neural network  
Keyword(2) SVM  
Keyword(3) fish image  
Keyword(4) Caffenet  
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1st Author's Name Kentaro Wakisaka  
1st Author's Affiliation Kyushu Institute of Technology (kyutech)
2nd Author's Name Takeshi Saitoh  
2nd Author's Affiliation Kyushu Institute of Technology (kyutech)
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Speaker Author-1 
Date Time 2016-02-21 09:30:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2015-132, CNR2015-33 
Volume (vol) vol.115 
Number (no) no.456(PRMU), no.457(CNR) 
Page pp.1-5 
#Pages
Date of Issue 2016-02-14 (PRMU, CNR) 


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