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Paper Abstract and Keywords
Presentation 2019-07-04 09:15
A Study on Feature quantities for Identification of fruit and flower by machine learning
Eisuke Fukuyama, Yuki Hosino, Takuya Sindo, Takefumi Hiraguri (NIT) CS2019-25
Abstract (in Japanese) (See Japanese page) 
(in English) In modern smart agriculture, technology has been developed to achieve farm work on instead of human by mechanization. However, the agriculture technique has required parts human vision, touch, and experience. These senses and experience work methods are realized using machine learning. In this paper, as one of efforts, we investigated the discrimination of tomato flowers and fruits using machine learning.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine learning / Image recognition / Identification / / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 101, CS2019-25, pp. 53-54, July 2019.
Paper # CS2019-25 
Date of Issue 2019-06-27 (CS) 
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 CS2019-25

Conference Information
Committee CS  
Conference Date 2019-07-04 - 2019-07-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Amami City Social Welfare Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Next Generation Networks, Access Networks, Broadband Access, Power Line Communications, Wireless Communication Systems, Coding Systems, etc. 
Paper Information
Registration To CS 
Conference Code 2019-07-CS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Feature quantities for Identification of fruit and flower by machine learning 
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Keyword(1) Machine learning  
Keyword(2) Image recognition  
Keyword(3) Identification  
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1st Author's Name Eisuke Fukuyama  
1st Author's Affiliation Nippon Institute of Technology (NIT)
2nd Author's Name Yuki Hosino  
2nd Author's Affiliation Nippon Institute of Technology (NIT)
3rd Author's Name Takuya Sindo  
3rd Author's Affiliation Nippon Institute of Technology (NIT)
4th Author's Name Takefumi Hiraguri  
4th Author's Affiliation Nippon Institute of Technology (NIT)
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Speaker Author-1 
Date Time 2019-07-04 09:15:00 
Presentation Time 15 minutes 
Registration for CS 
Paper # CS2019-25 
Volume (vol) vol.119 
Number (no) no.101 
Page pp.53-54 
#Pages
Date of Issue 2019-06-27 (CS) 


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