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Paper Abstract and Keywords
Presentation 2022-06-10 13:00
[Tutorial Lecture] How to build a High-Precision and Efficient Robot Vision: Dataset Generation and Hardware Implementation for Deep Learning
Hakaru Tamukoh (Kyutech) SIS2022-10
Abstract (in Japanese) (See Japanese page) 
(in English) This tutorial lecture explains a construction method for high-precision and efficient robot vision that includes a semi-automatic dataset generation method and an implementation method of deep neural networks (DNNs) on field-programmable gate arrays (FPGAs). The proposed dataset generation method ultimately reduces the time-consuming manual annotation process, and a generated dataset for DNNs can be prepared in about two hours. I show the evaluation results for a DNN trained by the generated dataset under real-world conditions through robot competitions such as RoboCup and World Robot Summit. We also show an example of FPGA implementation of YOLO v3 tiny. Through this presentation, I show examples of solutions for dataset preparation and power-consumption issues, which are significant barriers to edge applications of artificial intelligence.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep Learning / DNN / Dataset / FPGA / Robot Vision / RoboCup / World Robot Summit /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 62, SIS2022-10, pp. 45-48, June 2022.
Paper # SIS2022-10 
Date of Issue 2022-06-02 (SIS) 
ISSN Print edition: ISSN 0913-5685  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 SIS2022-10

Conference Information
Committee SIS IPSJ-AVM  
Conference Date 2022-06-09 - 2022-06-10 
Place (in Japanese) (See Japanese page) 
Place (in English) KIT(Wakamatsu Campus) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Intelligent Multimedia Systems, Applied Embedded Systems, Three-Dimensional Image Technology (3DIT), etc. 
Paper Information
Registration To SIS 
Conference Code 2022-06-SIS-AVM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) How to build a High-Precision and Efficient Robot Vision: Dataset Generation and Hardware Implementation for Deep Learning 
Sub Title (in English)  
Keyword(1) Deep Learning  
Keyword(2) DNN  
Keyword(3) Dataset  
Keyword(4) FPGA  
Keyword(5) Robot Vision  
Keyword(6) RoboCup  
Keyword(7) World Robot Summit  
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1st Author's Name Hakaru Tamukoh  
1st Author's Affiliation Kyushu Institute of Technology (Kyutech)
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Date Time 2022-06-10 13:00:00 
Presentation Time 40 minutes 
Registration for SIS 
Paper # SIS2022-10 
Volume (vol) vol.122 
Number (no) no.62 
Page pp.45-48 
#Pages
Date of Issue 2022-06-02 (SIS) 


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