Hybrid transfer learning strategy for cross-subject EEG emotion recognition

• Published in: Frontiers in human neuroscience Vol. 17; p. 1280241
• Main Authors: Lu, Wei, Liu, Haiyan, Ma, Hua, Tan, Tien-Ping, Xia, Lingnan
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 16.11.2023; Frontiers Media S.A
• Subjects: Ablation; Accuracy; Adaptability; Adaptation; Adaptive learning; affective computing; Algorithms; cross-subject EEG emotion recognition; Deep learning; domain adaptation; EEG; Electroencephalography; Emotions; few-shot; fine-tuning; Human Neuroscience; Investigations; Machine learning; Physiology; Support vector machines; Transfer learning; few-shot; fine-tuning; domain adaptation; affective computing; cross-subject EEG emotion recognition

Emotion recognition constitutes a pivotal research topic within affective computing, owing to its potential applications across various domains. Currently, emotion recognition methods based on deep learning frameworks utilizing electroencephalogram (EEG) signals have demonstrated effective applicati...