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Paper Abstract and Keywords
Presentation 2025-06-21 11:20
Domain adaptation of Spiking Neural Network using firing threshhold and leak parameters
Layla Chadaporn Antaket, Shiori Sugimoto, Kazuya Hayase, Masaki Kitahara (NTT) NC2025-3 IBISML2025-3
Abstract (in Japanese) (See Japanese page) 
(in English) This paper aims at domain adaptation by updating only a part of parameters of the SNN model in order to make the SNN model fast domain adaptation using very small amount of data. Parameters such as threshold and leak of membrane potential which decided the activation state of the neuron were noticed as the parameter to be renewed. Experimental results show that the trained SNN model for optical flow inference improves the inference performance for the same domain data by fine-tuning only the neuron activation parameter to the data of the domain to be applied. By this, it was proven that domain adaptation of arbitrary data was possible only by the activation parameter..
Keyword (in Japanese) (See Japanese page) 
(in English) Domain adaptation / Spiking Neural Network / Neuromorphic / / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 81, NC2025-3, pp. 8-13, June 2025.
Paper # NC2025-3 
Date of Issue 2025-06-14 (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 NC2025-3 IBISML2025-3

Conference Information
Committee NC IBISML IPSJ-BIO IPSJ-MPS  
Conference Date 2025-06-21 - 2025-06-23 
Place (in Japanese) (See Japanese page) 
Place (in English) Univ. Ryukyus 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2025-06-NC-IBISML-BIO-MPS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Domain adaptation of Spiking Neural Network using firing threshhold and leak parameters 
Sub Title (in English)  
Keyword(1) Domain adaptation  
Keyword(2) Spiking Neural Network  
Keyword(3) Neuromorphic  
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1st Author's Name Layla Chadaporn Antaket  
1st Author's Affiliation NTT Computer and Data Science Laboratories (NTT)
2nd Author's Name Shiori Sugimoto  
2nd Author's Affiliation NTT Computer and Data Science Laboratories (NTT)
3rd Author's Name Kazuya Hayase  
3rd Author's Affiliation NTT Computer and Data Science Laboratories (NTT)
4th Author's Name Masaki Kitahara  
4th Author's Affiliation NTT Computer and Data Science Laboratories (NTT)
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Speaker Author-1 
Date Time 2025-06-21 11:20:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2025-3, IBISML2025-3 
Volume (vol) vol.125 
Number (no) no.81(NC), no.82(IBISML) 
Page pp.8-13 
#Pages 6 
Date of Issue 2025-06-14 (NC, IBISML) 

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