IEICE Technical Committee Submission System
Conference Paper's Information		 Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2017-02-21 09:00
A Comparative Evaluation of Deep Features -- Classifier-based Learning vs. Distance Metric Learning. --
Shota Horiguchi, Daiki Ikami, Kiyoharu Aizawa (UTokyo)
Abstract (in Japanese) (See Japanese page) 
(in English) The extraction of useful deep features is important for many computer vision tasks. Deep features extracted from classification networks have proved to perform well in those tasks. On the other hand, end-to-end distance metric learning (DML) has been applied to train the feature extractor directly. However, many researches on DML did not make equitable comparisons to features extracted from classification networks, thus it is still unclear which training strategy is superior for learning feature representations. In this paper, by presenting objective comparisons between these two approaches under the same network architecture, we show that the softmax-based features are markedly better than DML features, especially when the dataset for training is large.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep feature / Softmax function / Distance metric learning / / / / /  
Reference Info. IEICE Tech. Rep.
Paper #  
Date of Issue  
ISSN  
Download PDF

Conference Information
Committee IE ITS ITE-AIT ITE-HI ITE-ME ITE-MMS ITE-CE  
Conference Date 2017-02-20 - 2017-02-21 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To ITE-ME 
Conference Code 2017-02-CE-MMS-AIT-HI-ME-ITS-IE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Comparative Evaluation of Deep Features 
Sub Title (in English) Classifier-based Learning vs. Distance Metric Learning. 
Keyword(1) Deep feature  
Keyword(2) Softmax function  
Keyword(3) Distance metric learning  
Keyword(4)  
Keyword(5)  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Shota Horiguchi  
1st Author's Affiliation The University of Tokyo (UTokyo)
2nd Author's Name Daiki Ikami  
2nd Author's Affiliation The University of Tokyo (UTokyo)
3rd Author's Name Kiyoharu Aizawa  
3rd Author's Affiliation The University of Tokyo (UTokyo)
4th Author's Name  
4th Author's Affiliation ()
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
Speaker Author-1 
Date Time 2017-02-21 09:00:00 
Presentation Time 15 minutes 
Registration for ITE-ME 
Paper #  
Volume (vol) vol.116 
Number (no)  
Page  
#Pages  
Date of Issue  

[Return to Top Page]

[Return to IEICE Web Page]
The Institute of Electronics, Information and Communication Engineers (IEICE), Japan