Learning a robust unified domain adaptation framework for cross-subject EEG-based emotion recognition
Over the last few years, unsupervised domain adaptation (UDA) based on deep learning has emerged as a solution to build cross-subject emotion recognition models from Electroencephalogram (EEG) signals, aligning the subject distributions within a latent feature space. However, most reported works hav...
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Published in | Biomedical signal processing and control Vol. 86; p. 105138 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.09.2023
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Subjects | |
Online Access | Get full text |
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