7 citations · 14 across the 7 of their papers we have counts for
3 papers · 1 filter
The role of data partitioning on the performance of EEG-based deep learning models in supervised cross-subject analysis: a preliminary study
Federico Del Pup, Andrea Zanola, Louis Fabrice Tshimanga +3
Deep learning is significantly advancing the analysis of electroencephalography (EEG) data by effectively discovering highly nonlinear patterns within the signals. Data partitionin…
The more, the better? Evaluating the role of EEG preprocessing for deep learning applications
Federico Del Pup, Andrea Zanola, Louis Fabrice Tshimanga +2
The last decade has witnessed a notable surge in deep learning applications for the analysis of electroencephalography (EEG) data, thanks to its demonstrated superiority over conve…
SelfEEG: A Python library for Self-Supervised Learning in Electroencephalography
Federico Del Pup, Andrea Zanola, Louis Fabrice Tshimanga +2
SelfEEG is an open-source Python library developed to assist researchers in conducting Self-Supervised Learning (SSL) experiments on electroencephalography (EEG) data. Its primary…