108 citations · 131 across the 10 of their papers we have counts for
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eess.SP2021★ 11 cited
Minimizing subject-dependent calibration for BCI with Riemannian transfer learning
Salim Khazem, Sylvain Chevallier, Quentin Barthélemy +2
Calibration is still an important issue for user experience in Brain-Computer Interfaces (BCI). Common experimental designs often involve a lengthy training period that raises the…
eess.SP2021★ 1 cited
RIGOLETTO -- RIemannian GeOmetry LEarning: applicaTion To cOnnectivity. A contribution to the Clinical BCI Challenge -- WCCI2020
Marie-Constance Corsi, Florian Yger, Sylvain Chevallier +1
This short technical report describes the approach submitted to the Clinical BCI Challenge-WCCI2020. This submission aims to classify motor imagery task from EEG signals and relies…