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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU 2022-09-14
10:15
Kanagawa
(Primary: On-site, Secondary: Online)
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
In this paper, we report the evaluation results of loss functions for low-resolution iris recognition using deep learnin... [more] PRMU2022-11
pp.7-12
PRMU 2021-12-16
11:00
Online Online Low-Resolution Iris Recognition with Image Super-Resolution for arbitrary magnification
Tsubasa Bora (UEC), Takahiro Toizumi, Yuho Shoji, Yuka Ogino, Masato Tsukada (NEC), Masatsugu Ichino (UEC) PRMU2021-26
A low-resolution iris image reduces iris recognition accuracy. Some conventional researches tackle low-resolution iris r... [more] PRMU2021-26
pp.13-18
PRMU 2021-08-26
16:00
Online Online A Study of Low-Resolution Iris Biometrics using Single Image Super-Resolution
Tsubasa Bora, Daisuke Uenoyama (UEC), Takahiro Toizumi, Yuka Ogino, Masato Tsukada (NEC), Masatsugu Ichino (UEC) PRMU2021-14
It requires a high-quality iris image in general, which means that subject must look into the camera, which is highly in... [more] PRMU2021-14
pp.42-47
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