Learning Subject-Generalized Topographical EEG Embeddings Using Deep Variational Autoencoders and Domain-Adversarial Regularization
Two of the biggest challenges in building models for detecting emotions from electroencephalography (EEG) devices are the relatively small amount of labeled samples and the strong variability of signal feature distributions between different subjects. In this study, we propose a context-generalized...
Main Authors: | Juan Lorenzo Hagad, Tsukasa Kimura, Ken-ichi Fukui, Masayuki Numao |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-03-01
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Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/5/1792 |
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