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Paper Abstract and Keywords
Presentation 2024-06-20 15:25
Selective Inference for Anomaly Detection using Diffusion Models
Teruyuki Katsuoka, Tomohiro Shiraishi (Nagoya Univ.), Daiki Miwa (NITech), Vo Nguyen Le Duy (RIKEN), Ichiro Takeuchi (Nagoya Univ./RIKEN) NC2024-9 IBISML2024-9
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, there has been active research on anomaly detection using diffusion models, which are generative models. These anomaly detection methods train the model using only normal images and generate virtual normal images for the input image to identify abnormal regions within the input. However, the reliability of the abnormal regions obtained in this way has not been sufficiently discussed. To address this problem, we propose an appropriate statistical hypothesis testing method that quantifies the reliability of the abnormal regions as a $p$-value using a selective inference framework, allowing for the control of the type I error rate. The validity of the proposed method is demonstrated through experiments on synthetic and real data.
Keyword (in Japanese) (See Japanese page) 
(in English) Generative Model / Diffusion Model / Anomaly Detection / Selective Inference / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 86, IBISML2024-9, pp. 60-66, June 2024.
Paper # IBISML2024-9 
Date of Issue 2024-06-13 (NC, 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 NC2024-9 IBISML2024-9

Conference Information
Committee IBISML NC IPSJ-BIO IPSJ-MPS  
Conference Date 2024-06-20 - 2024-06-22 
Place (in Japanese) (See Japanese page) 
Place (in English) OIST 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IBISML 
Conference Code 2024-06-IBISML-NC-BIO-MPS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Selective Inference for Anomaly Detection using Diffusion Models 
Sub Title (in English)  
Keyword(1) Generative Model  
Keyword(2) Diffusion Model  
Keyword(3) Anomaly Detection  
Keyword(4) Selective Inference  
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1st Author's Name Teruyuki Katsuoka  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Tomohiro Shiraishi  
2nd Author's Affiliation Nagoya University (Nagoya Univ.)
3rd Author's Name Daiki Miwa  
3rd Author's Affiliation Nagoya Institute of Technology (NITech)
4th Author's Name Vo Nguyen Le Duy  
4th Author's Affiliation RIKEN (RIKEN)
5th Author's Name Ichiro Takeuchi  
5th Author's Affiliation Nagoya University/RIKEN (Nagoya Univ./RIKEN)
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Speaker Author-1 
Date Time 2024-06-20 15:25:00 
Presentation Time 25 minutes 
Registration for IBISML 
Paper # NC2024-9, IBISML2024-9 
Volume (vol) vol.124 
Number (no) no.85(NC), no.86(IBISML) 
Page pp.60-66 
#Pages 7 
Date of Issue 2024-06-13 (NC, IBISML) 

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