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Paper Abstract and Keywords
Presentation 2022-05-27 14:55
Research on work support for assembly processes using deep learning technology
Takao Inoue (SYSTEC INOUE) LOIS2022-2
Abstract (in Japanese) (See Japanese page) 
(in English) Development of human resources, which is a strength of Japanese SMEs, In order to support work by the assembly process for the work of newcomers. From deep learning using YOLO, work procedures are combined with the arrangement of objects in manufacturing. Is it possible to support work by performing object detection? We conducted an evaluation experiment and studied the usefulness of the method.
Keyword (in Japanese) (See Japanese page) 
(in English) deep learning / work support / assembly process / / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 47, LOIS2022-2, pp. 7-10, May 2022.
Paper # LOIS2022-2 
Date of Issue 2022-05-19 (LOIS) 
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
Conference Date 2022-05-26 - 2022-05-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To LOIS 
Conference Code 2022-05-LOIS-SPT-GN 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Research on work support for assembly processes using deep learning technology 
Sub Title (in English)  
Keyword(1) deep learning  
Keyword(2) work support  
Keyword(3) assembly process  
1st Author's Name Takao Inoue  
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Speaker Author-1 
Date Time 2022-05-27 14:55:00 
Presentation Time 25 minutes 
Registration for LOIS 
Paper # LOIS2022-2 
Volume (vol) vol.122 
Number (no) no.47 
Page pp.7-10 
Date of Issue 2022-05-19 (LOIS) 

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