Paper Abstract and Keywords |
Presentation |
2022-09-14 10:15
Evaluation of Loss Functions for Low-Resolution Iris Recognition Using Deep Learning Rikuto Otsuka, Tsubasa Bora (UEC), Yuho Shoji, Yuka Ogino, Takahiro Toizumi (NEC), Ichino Masatsugu (UEC) PRMU2022-11 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In this paper, we report the evaluation results of loss functions for low-resolution iris recognition using deep learning. In recent years, many loss functions for feature extractors using deep learning have been proposed, particularly on face recognition. On the other hand, unlike face recognition, research on iris recognition has a problem that loss functions have not been enough compared or investigated. Therefore, in this paper, we train feature extractors for iris recognition by using 12 types of loss functions proposed for face recognition and compare their performance. Furthermore, we search loss functions that are robust to low-resolution iris recognition by downsampling the resolution of the input images. The evaluation results show that CosFace is the best loss function on large datasets and Triplet loss is the best on small datasets for low-resolution iris recognition. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Iris Recognition / Low-Resolution Iris Recognition / Loss Function / Deep Learning / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 181, PRMU2022-11, pp. 7-12, Sept. 2022. |
Paper # |
PRMU2022-11 |
Date of Issue |
2022-09-07 (PRMU) |
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 |
PRMU2022-11 |
Conference Information |
Committee |
PRMU |
Conference Date |
2022-09-14 - 2022-09-15 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
|
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Deep generative model |
Paper Information |
Registration To |
PRMU |
Conference Code |
2022-09-PRMU |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Evaluation of Loss Functions for Low-Resolution Iris Recognition Using Deep Learning |
Sub Title (in English) |
|
Keyword(1) |
Iris Recognition |
Keyword(2) |
Low-Resolution Iris Recognition |
Keyword(3) |
Loss Function |
Keyword(4) |
Deep Learning |
Keyword(5) |
|
Keyword(6) |
|
Keyword(7) |
|
Keyword(8) |
|
1st Author's Name |
Rikuto Otsuka |
1st Author's Affiliation |
The University of Electro-Communications (UEC) |
2nd Author's Name |
Tsubasa Bora |
2nd Author's Affiliation |
The University of Electro-Communications (UEC) |
3rd Author's Name |
Yuho Shoji |
3rd Author's Affiliation |
NEC Corporation (NEC) |
4th Author's Name |
Yuka Ogino |
4th Author's Affiliation |
NEC Corporation (NEC) |
5th Author's Name |
Takahiro Toizumi |
5th Author's Affiliation |
NEC Corporation (NEC) |
6th Author's Name |
Ichino Masatsugu |
6th Author's Affiliation |
The University of Electro-Communications (UEC) |
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 |
2022-09-14 10:15:00 |
Presentation Time |
15 minutes |
Registration for |
PRMU |
Paper # |
PRMU2022-11 |
Volume (vol) |
vol.122 |
Number (no) |
no.181 |
Page |
pp.7-12 |
#Pages |
6 |
Date of Issue |
2022-09-07 (PRMU) |
|