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Found 2 papers, 2 papers with code
EEG-Deformer: A Dense Convolutional Transformer for Brain-computer Interfaces
Effectively learning the temporal dynamics in electroencephalogram (EEG) signals is challenging yet essential for decoding brain activities using brain-computer interfaces (BCIs).
LGGNet: Learning from Local-Global-Graph Representations for Brain-Computer Interface
It captures temporal dynamics of EEG which then serves as input to the proposed local and global graph-filtering layers.
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