A neuroscience-inspired staged framework with dual-level semantic disentanglement and semantic latent channels improves EEG visual decoding performance on the THINGS-EEG benchmark under zero-shot settings.
Brainalign: Eeg-vision alignment via frequency- aware temporal encoder and differentiable cluster assigner, in: MIC- CAI, Springer
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Neuroscience-inspired Staged Representation Learning with Disentangled Coarse- and Fine-Grained Semantics for EEG Visual Decoding
A neuroscience-inspired staged framework with dual-level semantic disentanglement and semantic latent channels improves EEG visual decoding performance on the THINGS-EEG benchmark under zero-shot settings.