Integrating Functional Connectivity and Domain Adaptation for Generalizable EEG Emotion Recognition
Recognizing emotions using EEG signals is difficult because EEG data is not stationary, has a low signal-to-noise ratio, and varies a lot between subjects. We present a new hybrid framework called CDA-GAF (Cross-Domain Adaptive Graph Attention Fusion) in this work. It combines the strengths of Graph...
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Published in | Bulletin of Scientific Research pp. 22 - 30 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
03.05.2025
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Online Access | Get full text |
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