Research on dynamic domain adaptation selective ensemble algorithm for cross-subject EEG emotion classification

Electroencephalogram (EEG) has become an important medium for emotion recognition research due to its high temporal resolution and noninvasive nature. However, significant differences among subjects in skull structure, EEG physiological characteristics, and emotional perception lead to strong hetero...

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Veröffentlicht in:	Journal of King Saud University. Computer and information sciences Jg. 37; H. 9; S. 292 - 20
Hauptverfasser:	Qin, Yuanxian, Li, Danyang, Qin, Xue, Li, Chunlong, Li, Jialin, Yuan, Jiafan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cham Springer International Publishing 01.11.2025 Springer Nature B.V Springer
Schlagworte:	Accuracy Adaptation Algorithms Classification Computer Imaging Computer Science Cross-subject Database Management Domain adaptation Effectiveness Electroencephalogram (EEG) Electroencephalography Emotion recognition Emotions Feature selection Heterogeneity Machine Learning Methods Neighborhoods Neural networks Optimization Original Paper Pattern Recognition and Graphics Physiology Selective ensemble Software Engineering/Programming and Operating Systems Systems and Data Security Temporal resolution Theory of Computation Vision Domain adaptation Emotion recognition Electroencephalogram (EEG) Selective ensemble Cross-subject
ISSN:	1319-1578, 2213-1248, 1319-1578
Online-Zugang:	Volltext
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