Multi-View Self-Supervised Domain Adaptation for EEG-Based Emotion Recognition

Research on emotion recognition based on EEG signals has made significant progress. Most of the existing studies have focused on supervised learning methods, but real-life data cannot meet the requirement of high quality with labels. In addition, EEG signals have individual variability and instabili...

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Veröffentlicht in:	IEEE transactions on affective computing Jg. 16; H. 4; S. 3055 - 3066
Hauptverfasser:	Zhang, Lu, Shi, Hanwen, Li, Ziyi, Zheng, Wei-Long, Lu, Bao-Liang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Adaptation Adaptation models Adaptive algorithms Brain modeling Calibration Data mining Data models Datasets domain adaptation EEG Electroencephalography Emotion recognition Emotions Experiments Feature extraction Machine learning Performance evaluation Self-supervised learning
ISSN:	1949-3045, 1949-3045
Online-Zugang:	Volltext
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