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Paper Abstract and Keywords
Presentation 2024-11-30 10:15
Disentangle Learning for Interactive Semiconductor Inspection Robust to Thin-Film Interference
Koki Mitsusada, Koji Kamma, Toshikazu Wada (Wakayama Univ.), Yasuhiro Hamada, Yoshinori Shimada, Takeshi Noguchi, Toshiyuki Okayama (Advanced System Solutions Co., Ltd.) PRMU2024-25
Abstract (in Japanese) (See Japanese page) 
(in English) In the semiconductor wafer inspection process, an intensity difference-based method is widely used, in which defects are detected based on pixel-wise intensity difference of the images of an investigated die and a regular die. However, this method suffers a high false positive rate caused by thin-film interference, a phenomenon of an uneven film thickness distribution on the wafer. We have already proposed a semiconductor wafer inspection system using DN4C, which performs anomaly detection based on user intent through interactive neural network training. In this paper, we introduce disentanglement learning to separate the effects of “thin-film interference” from “semiconductor anomalies,” thereby improving the anomaly detection accuracy of DN4C. In the experiments, we confirmed the effectiveness of the proposed method by comparing semiconductor wafer images with varying film thickness, both with and without the application of disentanglement learning.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep Neural Network / Human in The Loop / Anormaly Detection / Thin-Film Interference / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 281, PRMU2024-25, pp. 93-98, Nov. 2024.
Paper # PRMU2024-25 
Date of Issue 2024-11-22 (PRMU) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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 PRMU2024-25

Conference Information
Committee PRMU IPSJ-CVIM IPSJ-CGVI IPSJ-DCC  
Conference Date 2024-11-29 - 2024-11-30 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2024-11-PRMU-CVIM-CGVI-DCC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Disentangle Learning for Interactive Semiconductor Inspection Robust to Thin-Film Interference 
Sub Title (in English)  
Keyword(1) Deep Neural Network  
Keyword(2) Human in The Loop  
Keyword(3) Anormaly Detection  
Keyword(4) Thin-Film Interference  
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1st Author's Name Koki Mitsusada  
1st Author's Affiliation Wakayama University (Wakayama Univ.)
2nd Author's Name Koji Kamma  
2nd Author's Affiliation Wakayama University (Wakayama Univ.)
3rd Author's Name Toshikazu Wada  
3rd Author's Affiliation Wakayama University (Wakayama Univ.)
4th Author's Name Yasuhiro Hamada  
4th Author's Affiliation SCREEN Advanced System Solutions Co., Ltd. (Advanced System Solutions Co., Ltd.)
5th Author's Name Yoshinori Shimada  
5th Author's Affiliation SCREEN Advanced System Solutions Co., Ltd. (Advanced System Solutions Co., Ltd.)
6th Author's Name Takeshi Noguchi  
6th Author's Affiliation SCREEN Advanced System Solutions Co., Ltd. (Advanced System Solutions Co., Ltd.)
7th Author's Name Toshiyuki Okayama  
7th Author's Affiliation SCREEN Advanced System Solutions Co., Ltd. (Advanced System Solutions Co., Ltd.)
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Speaker Author-1 
Date Time 2024-11-30 10:15:00 
Presentation Time 15 minutes 
Registration for PRMU 
Paper # PRMU2024-25 
Volume (vol) vol.124 
Number (no) no.281 
Page pp.93-98 
#Pages 6 
Date of Issue 2024-11-22 (PRMU) 

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