This study introduces TFCA-TransNet, a deep learning framework for individual EEG-MI signal classification. It combines FFT-derived features, CNN with Channel Attention, and a Transformer encoder to enhance feature representation, culminating in an efficient classifier with a fully connected layer.
☆20Dec 5, 2025Updated 10 months ago
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