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Paper Abstract and Keywords
Presentation 2023-12-20 14:55
Anomaly Detection by One-class Convolution Extreme Learning Machine Using Multiple Kernel
Yuta Okami, Takuya Kitamura (NIT, Toyama College) IBISML2023-31
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose a one-class convolutional extreme learning machine using multiple kernel. In this method, for anomaly detection problem with image data, different filters of a convolution layer are optimized by ELM autoencoders using different kernel, individually. Then, we combine the extracted images, and iterate these process several times. After this iteration, OC-KELM is trained with the extracted image. By this method, the learning cost can be reduced because it is not necessary to select a kernel parameter.
Keyword (in Japanese) (See Japanese page) 
(in English) Extreme learning machine / Convolutional layer / Anomaly detection / Multiple kernel / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 311, IBISML2023-31, pp. 7-12, Dec. 2023.
Paper # IBISML2023-31 
Date of Issue 2023-12-13 (IBISML) 
ISSN 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 IBISML2023-31

Conference Information
Committee IBISML  
Conference Date 2023-12-20 - 2023-12-21 
Place (in Japanese) (See Japanese page) 
Place (in English) National Institute of Informatics 
Topics (in Japanese) (See Japanese page) 
Topics (in English) machine learning, etc. 
Paper Information
Registration To IBISML 
Conference Code 2023-12-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Anomaly Detection by One-class Convolution Extreme Learning Machine Using Multiple Kernel 
Sub Title (in English)  
Keyword(1) Extreme learning machine  
Keyword(2) Convolutional layer  
Keyword(3) Anomaly detection  
Keyword(4) Multiple kernel  
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1st Author's Name Yuta Okami  
1st Author's Affiliation National Institute of Technology, Toyama College (NIT, Toyama College)
2nd Author's Name Takuya Kitamura  
2nd Author's Affiliation National Institute of Technology, Toyama College (NIT, Toyama College)
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Speaker Author-1 
Date Time 2023-12-20 14:55:00 
Presentation Time 25 minutes 
Registration for IBISML 
Paper # IBISML2023-31 
Volume (vol) vol.123 
Number (no) no.311 
Page pp.7-12 
#Pages 6 
Date of Issue 2023-12-13 (IBISML) 

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