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of 9
pro vyhledávání: '"Ebihara, Akinori F."'
Theoretically-inspired sequential density ratio estimation (SDRE) algorithms are proposed for the early classification of time series. Conventional SDRE algorithms can fail to estimate DRs precisely due to the internal overnormalization problem, whic
Externí odkaz:
http://arxiv.org/abs/2302.09810
Time series data are often obtained only within a limited time range due to interruptions during observation process. To classify such partial time series, we need to account for 1) the variable-length data drawn from 2) different timestamps. To addr
Externí odkaz:
http://arxiv.org/abs/2207.03718
Autor:
Miyamoto, Takaya, Hashimoto, Hiroshi, Hayasaka, Akihiro, Ebihara, Akinori F., Imaoka, Hitoshi
Publikováno v:
2021 IEEE International Joint Conference on Biometrics (IJCB), 2021, pp. 1-8
Face recognition for visible light (VIS) images achieve high accuracy thanks to the recent development of deep learning. However, heterogeneous face recognition (HFR), which is a face matching in different domains, is still a difficult task due to th
Externí odkaz:
http://arxiv.org/abs/2204.11434
The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization
Autor:
Miyagawa, Taiki, Ebihara, Akinori F.
We propose a model for multiclass classification of time series to make a prediction as early and as accurate as possible. The matrix sequential probability ratio test (MSPRT) is known to be asymptotically optimal for this setting, but contains a cri
Externí odkaz:
http://arxiv.org/abs/2105.13636
Classifying sequential data as early and as accurately as possible is a challenging yet critical problem, especially when a sampling cost is high. One algorithm that achieves this goal is the sequential probability ratio test (SPRT), which is known a
Externí odkaz:
http://arxiv.org/abs/2006.05587
In light of the rising demand for biometric-authentication systems, preventing face spoofing attacks is a critical issue for the safe deployment of face recognition systems. Here, we propose an efficient face presentation attack detection (PAD) algor
Externí odkaz:
http://arxiv.org/abs/1907.12400
Akademický článek
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Akademický článek
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Autor:
Schmehl MN, Caruso VC, Chen Y, Jun NY, Willett SM, Mohl JT, Ruff DA, Cohen M, Ebihara AF, Freiwald W, Tokdar ST, Groh JM
Publikováno v:
BioRxiv : the preprint server for biology [bioRxiv] 2023 Jul 19. Date of Electronic Publication: 2023 Jul 19.
