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Paper Abstract and Keywords
Presentation 2020-02-27 09:45
Fish body measurement by depth estimation for automatic feeding of aquaculture
Kaito Hattori, Nobuo Ezaki, Motonori Saeki (NITTC), Osamu Takahashi (ISE C.L), Tatsuhiko Sakamoto (Mie Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) In the automatic feeding system for aquaculture such as red sea snapper and yellowtail, the amount of feed is calculated based on fish weight and water temperature, so it is important to grasp fish weight. However, it is not realistic to use frequently a weighing scale, which is a general method of measuring fish, because it is a task that stresses the fish. Furthermore, it is one of the causes of lowering the commercial value, such as the fish coming into contact with the net and being damaged when they are taken out of the fish cage. Therefore, in this research, we propose a mechanism that can predict the distance to fish using depth estimation by machine learning and measure fish length from single image. As a result, it is possible to always measure fish, and it is expected that the accuracy of calculating the amount of feed will be greatly improved.
Keyword (in Japanese) (See Japanese page) 
(in English) Sea Farmers / Aquaculture management / Fish measurement / Artificial intelligence / Depth prediction / / /  
Reference Info. ITE Tech. Rep., vol. 44, no. 6, ME2020-29, pp. 1-5, Feb. 2020.
Paper # ME2020-29 
Date of Issue 2020-02-20 (MMS, HI, ME, AIT) 
ISSN Print edition: ISSN 1342-6893  Online edition: ISSN 2424-1970
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Conference Information
Committee HI IEICE-IE IEICE-ITS MMS ME AIT  
Conference Date 2020-02-27 - 2020-02-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To ME 
Conference Code 2020-02-HI-IE-ITS-MMS-ME-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Fish body measurement by depth estimation for automatic feeding of aquaculture 
Sub Title (in English)  
Keyword(1) Sea Farmers  
Keyword(2) Aquaculture management  
Keyword(3) Fish measurement  
Keyword(4) Artificial intelligence  
Keyword(5) Depth prediction  
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1st Author's Name Kaito Hattori  
1st Author's Affiliation National Institute of Technology, Toba College (NITTC)
2nd Author's Name Nobuo Ezaki  
2nd Author's Affiliation National Institute of Technology, Toba College (NITTC)
3rd Author's Name Motonori Saeki  
3rd Author's Affiliation National Institute of Technology, Toba College (NITTC)
4th Author's Name Osamu Takahashi  
4th Author's Affiliation ISE Co. Ltd. (ISE C.L)
5th Author's Name Tatsuhiko Sakamoto  
5th Author's Affiliation Mie University (Mie Univ.)
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Speaker
Date Time 2020-02-27 09:45:00 
Presentation Time 15 
Registration for ME 
Paper # ITE-MMS2020-1,ITE-HI2020-1,ITE-ME2020-29,ITE-AIT2020-1 
Volume (vol) ITE-44 
Number (no) no.6 
Page pp.1-5 
#Pages ITE-5 
Date of Issue ITE-MMS-2020-02-20,ITE-HI-2020-02-20,ITE-ME-2020-02-20,ITE-AIT-2020-02-20 


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