A DWT-gated transformer EEG encoder with CLIP alignment and category-aware clustering loss generates semantic images via a pre-trained diffusion model, achieving 43% max single-subject top-1 classification accuracy and a new WordNet-based semantic score.
Brain2image: Converting brain signals into images
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Category-aware EEG image generation based on wavelet transform and contrast semantic loss
A DWT-gated transformer EEG encoder with CLIP alignment and category-aware clustering loss generates semantic images via a pre-trained diffusion model, achieving 43% max single-subject top-1 classification accuracy and a new WordNet-based semantic score.