MFENet: A Multi-Feature Extraction Network for Enhanced Emotion Detection Using EEG and STFT
Developing computationally efficient models for EEG-based emotion recognition is essential for enabling scalable and responsive brain-computer interface (BCI) systems. However, the inherent nonstationarity of EEG signals and individual variability across subjects complicate the development of models...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11087487/ |
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