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pro vyhledávání: '"Ko, Wonjun"'
Sleep staging is essential for sleep assessment and plays a vital role as a health indicator. Many recent studies have devised various machine learning as well as deep learning architectures for sleep staging. However, two key challenges hinder the p
Externí odkaz:
http://arxiv.org/abs/2203.12590
Modeling non-Euclidean data is drawing extensive attention along with the unprecedented successes of deep neural networks in diverse fields. Particularly, a symmetric positive definite matrix is being actively studied in computer vision, signal proce
Externí odkaz:
http://arxiv.org/abs/2112.03379
In this work, we formulate the problem of estimating and selecting task-relevant temporal signal segments from a single EEG trial in the form of a Markov decision process and propose a novel reinforcement-learning mechanism that can be combined with
Externí odkaz:
http://arxiv.org/abs/2007.00162
Recent advances in deep learning have had a methodological and practical impact on brain-computer interface research. Among the various deep network architectures, convolutional neural networks have been well suited for spatio-spectral-temporal elect
Externí odkaz:
http://arxiv.org/abs/2003.02657
In recent years, deep learning-based feature representation methods have shown a promising impact in electroencephalography (EEG)-based brain-computer interface (BCI). Nonetheless, owing to high intra- and inter-subject variabilities, many studies on
Externí odkaz:
http://arxiv.org/abs/1910.07747
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Akademický článek
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Autor:
Min, Byoung-Kyong, Kim, Hyun-Seok, Ko, Wonjun, Ahn, Min-Hee, Suk, Heung-Il, Pantazis, Dimitrios, Knight, Robert T.
Publikováno v:
In NeuroImage 15 August 2021 237
Publikováno v:
In NeuroImage 1 August 2021 236
Publikováno v:
In Deep Learning for Medical Image Analysis Edition: Second Edition. 2024:3-31