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Found 2 papers, 1 papers with code
Decoding visual brain representations from electroencephalography through Knowledge Distillation and latent diffusion models
Additionally, we incorporated an image reconstruction mechanism based on pre-trained latent diffusion models, which allowed us to generate an estimate of the images which had elicited EEG activity.
An intertwined neural network model for EEG classification in brain-computer interfaces
In this paper, we present a deep neural network architecture specifically engineered to a) provide state-of-the-art performance in multiclass motor imagery classification and b) remain robust to preprocessing to enable real-time processing of raw data as it streams from EEG and BCI equipment.
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