RMETNet: A cross-subject motor imagery EEG signal classification model based on TSLANet and riemannian geometry features.
RMETNet enhances MI-EEG classification, achieving 71.39% accuracy across subjects. Key features include TSLANet and Riemannian geometry. 📊🧠
