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Paper Abstract and Keywords
Presentation 2024-01-25 09:00
The Relationship Between Metrics in the Latent Variable Space and Image Classification Performance
Haruki Wakasa, Kenya Jin'no (Tokyo City Univ.) NLP2023-99 MICT2023-54 MBE2023-45
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, models based on convolutional neural networks (CNNs) have exhibited high performance in image classification, but it is thought that the general training with Cross Entropy Loss using Softmax function does not take into account class separation and data variance in the latent variable space. This is thought to be the cause of misclassification.
This study aims to clarify the effect of Center Loss, a method of Deep Metric Learning, on latent variable space and image classification accuracy.
Experimental results suggest that while Center Loss learns a latent variable space with high image classification accuracy using Euclidean distance, it may have a negative impact on learning in Softmax function and Cross Entropy Loss.
Keyword (in Japanese) (See Japanese page) 
(in English) Image classification / Deep metric learning / Latent variable space / Convolutional neural networks / Silhouette analysis / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 354, NLP2023-99, pp. 78-81, Jan. 2024.
Paper # NLP2023-99 
Date of Issue 2024-01-17 (NLP, MICT, MBE) 
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 NLP2023-99 MICT2023-54 MBE2023-45

Conference Information
Committee NC MBE NLP MICT  
Conference Date 2024-01-24 - 2024-01-25 
Place (in Japanese) (See Japanese page) 
Place (in English) Naruto University of Education 
Topics (in Japanese) (See Japanese page) 
Topics (in English) NC, MBE, MICT, NLP, etc. 
Paper Information
Registration To NLP 
Conference Code 2024-01-NC-MBE-NLP-MICT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) The Relationship Between Metrics in the Latent Variable Space and Image Classification Performance 
Sub Title (in English)  
Keyword(1) Image classification  
Keyword(2) Deep metric learning  
Keyword(3) Latent variable space  
Keyword(4) Convolutional neural networks  
Keyword(5) Silhouette analysis  
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Keyword(7)  
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1st Author's Name Haruki Wakasa  
1st Author's Affiliation Tokyo City University (Tokyo City Univ.)
2nd Author's Name Kenya Jin'no  
2nd Author's Affiliation Tokyo City University (Tokyo City Univ.)
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Speaker Author-1 
Date Time 2024-01-25 09:00:00 
Presentation Time 20 minutes 
Registration for NLP 
Paper # NLP2023-99, MICT2023-54, MBE2023-45 
Volume (vol) vol.123 
Number (no) no.354(NLP), no.355(MICT), no.356(MBE) 
Page pp.78-81 
#Pages 4 
Date of Issue 2024-01-17 (NLP, MICT, MBE) 

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