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Paper Abstract and Keywords
Presentation 2023-03-16 14:25
Pear flower pollination path estimation using deep learning and combinatorial optimization
Keita Endo (NIT), Tomotaka Kimura (Doshisha Univ.), Hiroyuki Shimizu (NIT), Tomohito Shimada, Akane Shibasaki (SATRC), Yoshihiro Takemura (Tottori Univ.), Takefumi Hiraguri (NIT) CQ2022-95
Abstract (in Japanese) (See Japanese page) 
(in English) Since fruit trees are grown outdoors, they require heavy and long hours working. In among fruit trees, pears needs artificial pollination, and labor saving is required. In this study, we propose the pollination systems that sprays pollen to pear flowers using a drone. In the proposed scheme, the drones takes an aerial image of the entire pear field from above, and by segmentation using deep learning, the range of the field and the space where the drone can fly are detected from the aerial image. Based on the detected results, image processing and combinatorial optimization are used to estimate the optimal route for autonomous flight that enables pollination work.
Keyword (in Japanese) (See Japanese page) 
(in English) Smart agriculture / Deep learning / Drones / Image analysis / Segmentation / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 438, CQ2022-95, pp. 74-77, March 2023.
Paper # CQ2022-95 
Date of Issue 2023-03-08 (CQ) 
ISSN Online edition: ISSN 2432-6380
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 IMQ IE MVE CQ  
Conference Date 2023-03-15 - 2023-03-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawaken Seinenkaikan (Naha-shi) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Media of five senses, Multimedia, Media experience, Picture codinge, Image media quality, Network,quality and reliability, etc(AC) 
Paper Information
Registration To CQ 
Conference Code 2023-03-IMQ-IE-MVE-CQ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Pear flower pollination path estimation using deep learning and combinatorial optimization 
Sub Title (in English)  
Keyword(1) Smart agriculture  
Keyword(2) Deep learning  
Keyword(3) Drones  
Keyword(4) Image analysis  
Keyword(5) Segmentation  
1st Author's Name Keita Endo  
1st Author's Affiliation Nippon Institute of Technology (NIT)
2nd Author's Name Tomotaka Kimura  
2nd Author's Affiliation Doshisha University (Doshisha Univ.)
3rd Author's Name Hiroyuki Shimizu  
3rd Author's Affiliation Nippon Institute of Technology (NIT)
4th Author's Name Tomohito Shimada  
4th Author's Affiliation Saitama Agricultural Technology Research Center (SATRC)
5th Author's Name Akane Shibasaki  
5th Author's Affiliation Saitama Agricultural Technology Research Center (SATRC)
6th Author's Name Yoshihiro Takemura  
6th Author's Affiliation Tottori University (Tottori Univ.)
7th Author's Name Takefumi Hiraguri  
7th Author's Affiliation Nippon Institute of Technology (NIT)
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Speaker Author-1 
Date Time 2023-03-16 14:25:00 
Presentation Time 25 minutes 
Registration for CQ 
Paper # CQ2022-95 
Volume (vol) vol.122 
Number (no) no.438 
Page pp.74-77 
Date of Issue 2023-03-08 (CQ) 

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