SwitchBraidNet is a compact dual-path EEG classifier achieving 69.49% MI accuracy (FP16), 93.48% SSVEP accuracy (FP32), 64.82 bits/min hybrid ITR (FP16), and 3.03 KB INT8 size via quantization-aware training on OpenBMI.
Exploring gaze-motor imagery hybrid brain-computer in- terface design.2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2014
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SwitchBraidNet: Quantisation-Aware Lightweight Architecture for Hybrid Brain-Computer Interface
SwitchBraidNet is a compact dual-path EEG classifier achieving 69.49% MI accuracy (FP16), 93.48% SSVEP accuracy (FP32), 64.82 bits/min hybrid ITR (FP16), and 3.03 KB INT8 size via quantization-aware training on OpenBMI.