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Hayato Maki
Hayato Maki
ZOZO Research
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EEG SIGNAL ENHANCEMENT USING MULTI-CHANNEL WIENER FILTER WITH A SPATIAL CORRELATION PRIOR
H Maki, T Toda, S Sakti, G Neubig, S Nakamura
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International …, 0
26*
Electroencephalogram-based single-trial detection of language expectation violations in listening to speech
H Tanaka, H Watanabe, H Maki, S Sakriani, S Nakamura
Frontiers in computational neuroscience 13, 15, 2019
132019
Electroencephalogram-based single-trial detection of language expectation violations in listening to speech
H Tanaka, H Watanabe, H Maki, S Sakriani, S Nakamura
Frontiers in computational neuroscience 13, 15, 2019
132019
Graph regularized tensor factorization for single-trial EEG analysis
H Maki, H Tanaka, S Sakti, S Nakamura
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
92018
Quality prediction of synthesized speech based on tensor structured EEG signals
H Maki, S Sakti, H Tanaka, S Nakamura
PloS one 13 (6), e0193521, 2018
72018
Enhancing Event-Related Potentials Based on Maximum a Posteriori Estimation with a Spatial Correlation Prior
H MAKI, T TODA, S SAKTI, G NEUBIG, S NAKAMURA
IEICE TRANSACTIONS on Information and Systems 99 (6), 1437-1446, 2016
42016
Single-trial detection of semantic anomalies from EEG during listening to spoken sentences
H Tanaka, H Watanabe, H Maki, S Sakti, S Nakamura
2018 40th Annual International Conference of the IEEE Engineering in …, 2018
32018
An Evaluation of EEG Ocular Artifact Removal with a Multi-channel Wiener Filter Based on Probabilistic Generative Model
H Maki, T Toda, S Sakti, G Neubig, S Nakamura
Proc. Int. Conf. of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015
32015
Removing noise from event-related potentials using a probabilistic generative model with grouped covariance matrices
H Maki, T Toda, S Sakti, G Neubig, S Nakamura
2016 38th Annual International Conference of the IEEE Engineering in …, 2016
12016
Probabilistic enhancement of EEG components using prior information of componentrelated spatial correlation
H Maki, T Toda, S Sakti, G Neubig, S Nakamura
Proc. Int. Conf. of the IEEE Engineering in Medicine and Biology Society (EMBC), 2014
12014
Noise-Removal From Electroencephalographies Toward Single-Trial Cognitive State Analysis
H Maki
Nara Institute of Science and Technology, 2018
2018
Tensor Factorization with Graph Structure for EEG Analysis
H Maki, H Tanaka, S Sakti, S Nakamura
IEICE Technical Report; IEICE Tech. Rep. 117 (507), 35-39, 2018
2018
Prediction of subjective rating values using EEG
H Maki, S Sakti, H Tanaka, S Nakamura
IEICE Technical Report; IEICE Tech. Rep. 117 (507), 113-118, 2018
2018
Discrimination of semantic violations from EEG during listening to spoken sentences
H Tanaka, H Watanabe, H Maki, S Sakriani, S Nakamura
IEICE Technical Report; IEICE Tech. Rep. 117 (375), 5-8, 2017
2017
Enhancement of Target Components in EEG Signals Based on A Probabilistic Generative Model Using Spatial Correlation Prior
H Maki
Nara Institute of Science and Technology, 2015
2015
Probabilistic Enhancement of EEG Component Using Prior Distribution of Correlations Between Channels
H Maki, T Toda, S Sakti, G Neubig, S Nakamura
IEICE Technical Report; IEICE Tech. Rep. 114 (104), 237-242, 2014
2014
ੜ׆ श׳΍ ମ࣭ͷσʔλΛ༻ ͍ͨͭ܏޲ ͷ༧ଌ
S Yamaguchi, H Tanaka, H Maki, S Kanaya, N Suzuki, S Nakamura
Prediction of Depressive Tendency from Multidimensional Health Data Collected through Crowdsourcing
S Yamaguchi, H Tanaka, H Maki, S Kanaya12, N Suzuki, S Nakamura12
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Artikelen 1–18