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Paper Abstract and Keywords
Presentation 2023-01-27 14:10
A study on the introduction of managerial workers in crime detection using crowdsourcing
Tomoya Nohara (Doshisha Univ.), Ryuya Itano, Takahiro Koita (Graduate School of Doshisha University) CAS2022-89 ICTSSL2022-53
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, the number of surveillance cameras installed has been increasing due to the spread of IoT, but there is a shortage of human resources to detect abnormalities from surveillance camera video. In a previous study, a crime detection method using crowdsourcing was proposed, but the low reliability of the response results and high cost were issues. In addition, in order to reduce the number of tasks assigned to workers, an attempt was made to remove easy tasks that do not require human judgment in advance using deep learning, but the current deep learning method does not provide sufficient accuracy. In this study, we aim to reduce the number of worker task assignments by introducing a highly reliable manager-worker that manages worker tasks. We then conducted a cost and cost-effectiveness analysis to determine whether the manager-worker method is more useful than the conventional method.
Keyword (in Japanese) (See Japanese page) 
(in English) Anomaly detection / Crowdsorcing / Manager worker / Amazon Mechanical Turk / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 361, ICTSSL2022-53, pp. 131-134, Jan. 2023.
Paper # ICTSSL2022-53 
Date of Issue 2023-01-19 (CAS, ICTSSL) 
ISSN Online edition: ISSN 2432-6380
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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 ICTSSL CAS  
Conference Date 2023-01-26 - 2023-01-27 
Place (in Japanese) (See Japanese page) 
Place (in English) TBD 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Student Session, General Session 
Paper Information
Registration To ICTSSL 
Conference Code 2023-01-ICTSSL-CAS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A study on the introduction of managerial workers in crime detection using crowdsourcing 
Sub Title (in English)  
Keyword(1) Anomaly detection  
Keyword(2) Crowdsorcing  
Keyword(3) Manager worker  
Keyword(4) Amazon Mechanical Turk  
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1st Author's Name Tomoya Nohara  
1st Author's Affiliation Doshisha University (Doshisha Univ.)
2nd Author's Name Ryuya Itano  
2nd Author's Affiliation Graduate School of Doshisha University (Graduate School of Doshisha University)
3rd Author's Name Takahiro Koita  
3rd Author's Affiliation Graduate School of Doshisha University (Graduate School of Doshisha University)
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Date Time 2023-01-27 14:10:00 
Presentation Time 20 minutes 
Registration for ICTSSL 
Paper # CAS2022-89, ICTSSL2022-53 
Volume (vol) vol.122 
Number (no) no.360(CAS), no.361(ICTSSL) 
Page pp.131-134 
#Pages
Date of Issue 2023-01-19 (CAS, ICTSSL) 


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