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Paper Abstract and Keywords
Presentation 2014-09-01 15:50
Fish species classification by the support vector machine
Atsushi Kinjo, Masanori Ito, Ikuo Matsuo (Tohoku Gakuin Univ.), Tomohito Imaizumi, Tomonari Akamatsu (FRA-NRI) PRMU2014-45 IBISML2014-26
Abstract (in Japanese) (See Japanese page) 
(in English) Fish species classification using echo-sounder is important for fisheries. With school of mixed species, it is necessary to extract individual fish echoes and to classify individual fish species from echoes. A broadband signal, which offered the advantage of high range resolution, was applied to detect individual fish for this purpose. The positions of fish were estimated from the time difference of arrivals by using the split-beam system. The target strength (TS) spectrum of individual fish echo was computed from the isolated echo and the estimated position. In this paper, the Support Vector Machine was introduced to classify fish species by using these TS spectra. In addition, it is well known that the TS spectra are dependent on not only fish species but also fish size. Therefore, it is necessary to classify both fish species and size by using these features. We tried to classify two species and two sizes of schools. Subject species were chub mackerel (Scomber japonicas) and Japanese jack mackerel (Trachurus japonicus). We calculated the classification rates. The fish species and size classification rate was about 67%. And, the fish species classification rate was about 80%.
Keyword (in Japanese) (See Japanese page) 
(in English) Fish species and size classification / Support Vector Machine / Target strength spectra / Broad-band split beam / / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 198, IBISML2014-26, pp. 57-62, Sept. 2014.
Paper # IBISML2014-26 
Date of Issue 2014-08-25 (PRMU, IBISML) 
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)
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Conference Information
Committee PRMU IBISML IPSJ-CVIM  
Conference Date 2014-09-01 - 2014-09-02 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To IBISML 
Conference Code 2014-09-PRMU-IBISML-CVIM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Fish species classification by the support vector machine 
Sub Title (in English)  
Keyword(1) Fish species and size classification  
Keyword(2) Support Vector Machine  
Keyword(3) Target strength spectra  
Keyword(4) Broad-band split beam  
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1st Author's Name Atsushi Kinjo  
1st Author's Affiliation Tohoku Gakuin University (Tohoku Gakuin Univ.)
2nd Author's Name Masanori Ito  
2nd Author's Affiliation Tohoku Gakuin University (Tohoku Gakuin Univ.)
3rd Author's Name Ikuo Matsuo  
3rd Author's Affiliation Tohoku Gakuin University (Tohoku Gakuin Univ.)
4th Author's Name Tomohito Imaizumi  
4th Author's Affiliation Fisheries Research Agency National Research Institute of Fisheries Engineering (FRA-NRI)
5th Author's Name Tomonari Akamatsu  
5th Author's Affiliation Fisheries Research Agency National Research Institute of Fisheries Engineering (FRA-NRI)
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Speaker Author-1 
Date Time 2014-09-01 15:50:00 
Presentation Time 30 minutes 
Registration for IBISML 
Paper # PRMU2014-45, IBISML2014-26 
Volume (vol) vol.114 
Number (no) no.197(PRMU), no.198(IBISML) 
Page pp.57-62 
#Pages
Date of Issue 2014-08-25 (PRMU, IBISML) 


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