IEEE23d
TRANSIT-EEG — A Framework for Cross-Subject Classification with Subject Specific Adaptation
Traditional EEG signal classification paradigms rely on extensive subject ... Also, it employs a robust Self Organising Graph Attention Transformer (SOGAT) that dynamically constructs a graph for each ...
EE Herald1y
Biomedical signal analysis
The recording of electrical signals emanated from human brain, which can be collected from the scalp of the head is called Electroencephalography (EEG). These signal's parameters and patterns indicate ...
GitHub1y
Silent EEG classification using cross-fusion adaptive graph convolution network for multilingual neurolinguistic signal decoding
Thank for citing our paper: @article{li2024silent, title={Silent EEG classification using cross-fusion adaptive graph convolution network for multilingual neurolinguistic signal decoding}, author={Li, ...
GitHub2y
README.md
TorchEEG provides plugins related to graph algorithms for converting EEG in datasets into ... torcheeg.transforms Extensive EEG preprocessing methods help users extract features, construct EEG signal ...
IEEE1y
Ramnivas Sharma
Brain Regions,EEG Data,EEG Signals,Eigenvalues,Graph Laplacian,Graph Signal,Graph Structure,Laplacian Matrix,Long Short-term Memory,Machine Learning,Nodes In The ...