most citedEEG_RL-Net: Enhancing EEG MI Classification through Reinforcement Learning-Optimised Graph Neural Networks

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

eess.SP2024★ 2 cited

EEG_RL-Net: Enhancing EEG MI Classification through Reinforcement Learning-Optimised Graph Neural Networks

Htoo Wai Aung, Jiao Jiao Li, Yang An +1

Brain-Computer Interfaces (BCIs) rely on accurately decoding electroencephalography (EEG) motor imagery (MI) signals for effective device control. Graph Neural Networks (GNNs) outp…

cs.LG2024

EEG_GLT-Net: Optimising EEG Graphs for Real-time Motor Imagery Signals Classification

Htoo Wai Aung, Jiao Jiao Li, Yang An +1

Brain-Computer Interfaces connect the brain to external control devices, necessitating the accurate translation of brain signals such as from electroencephalography (EEG) into exec…