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Found 5 papers, 1 papers with code
Alljoined -- A dataset for EEG-to-Image decoding
We present Alljoined, a dataset built specifically for EEG-to-Image decoding.
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
The significance of this study lies in its contribution to establishing a rigorous and transparent benchmark for BCI research, offering insights into optimal methodologies and highlighting the importance of reproducibility in driving advancements within the field.
Geometric Neural Network based on Phase Space for BCI decoding
\textbf{Approach:} Our research aims to develop a DL algorithm that delivers effective results with a limited number of electrodes.
A Systematic Evaluation of Euclidean Alignment with Deep Learning for EEG Decoding
In this work, we systematically evaluate the effect of EA combined with DL for decoding BCI signals.
Evaluating the structure of cognitive tasks with transfer learning
While transfer learning is a promising technique to address this challenge, it assumes that transferable data domains and task are known, which is not the case in this setting.
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