37 citations · 63 across the 6 of their papers we have counts for
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eess.SP2020★ 1 cited
Comparison of Attention-based Deep Learning Models for EEG Classification
Giulia Cisotto, Alessio Zanga, Joanna Chlebus +3
Objective: To evaluate the impact on Electroencephalography (EEG) classification of different kinds of attention mechanisms in Deep Learning (DL) models. Methods: We compared three…
eess.SP2020★ 37 cited
Deep learning-based classification of fine hand movements from low frequency EEG
Giulia Bressan, Selina C. Wriessnegger, Giulia Cisotto
The classification of different fine hand movements from EEG signals represents a relevant research challenge, e.g., in brain-computer interface applications for motor rehabilitati…
eess.SP2020
REPAC: Reliable estimation of phase-amplitude coupling in brain networks
Giulia Cisotto
Recent evidence has revealed cross-frequency coupling and, particularly, phase-amplitude coupling (PAC) as an important strategy for the brain to accomplish a variety of high-level…