most citedEEG-Transformer: Self-attention from Transformer Architecture for Decoding EEG of Imagined Speech

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eess.AS2023

Diff-E: Diffusion-based Learning for Decoding Imagined Speech EEG

Soowon Kim, Young-Eun Lee, Seo-Hyun Lee +1

Decoding EEG signals for imagined speech is a challenging task due to the high-dimensional nature of the data and low signal-to-noise ratio. In recent years, denoising diffusion pr…