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Paper Abstract and Keywords
Presentation 2024-02-10 09:45
A Study of Work Time Reduction Methods for Individual Recognition in Zoo
Kanon Shimodaira, Ayana Rikimaru (NIT,NC)
Abstract (in Japanese) (See Japanese page) 
(in English) This study investigated the feasibility of a real-time recognition system with the goal of improving the experience of observing animals in zoo. Birds were detected from images using an existing object detection model, and the type of bird was recognized using image classification. Recognition rate comparisons were made for five different bird species between this method and the object detection. This method produced better results than existing object detection methods that require long preparation times. Future efforts will be made to improve the accuracy of the system for implementation of individual bird identification.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine Learning / Object Detection / Image Classification / Individual Recognition / / / /  
Reference Info. ITE Tech. Rep., vol. 48, no. 4, ME2024-1, pp. 1-3, Feb. 2024.
Paper # ME2024-1 
Date of Issue 2024-02-03 (ME) 
ISSN Online edition: ISSN 2424-1970
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Conference Information
Committee ME  
Conference Date 2024-02-10 - 2024-02-10 
Place (in Japanese) (See Japanese page) 
Place (in English) online 
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Paper Information
Registration To ME 
Conference Code 2024-02-ME 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study of Work Time Reduction Methods for Individual Recognition in Zoo 
Sub Title (in English)  
Keyword(1) Machine Learning  
Keyword(2) Object Detection  
Keyword(3) Image Classification  
Keyword(4) Individual Recognition  
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1st Author's Name Kanon Shimodaira  
1st Author's Affiliation National Institute of Technology(KOSEN), Nagano College (NIT,NC)
2nd Author's Name Ayana Rikimaru  
2nd Author's Affiliation National Institute of Technology(KOSEN), Nagano College (NIT,NC)
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Speaker Author-1 
Date Time 2024-02-10 09:45:00 
Presentation Time 15 minutes 
Registration for ME 
Paper # ME2024-1 
Volume (vol) vol.48 
Number (no) no.4 
Page pp.1-3 
#Pages
Date of Issue 2024-02-03 (ME) 


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