7 citations · 14 across the 6 of their papers we have counts for
3 papers · 1 filter
TransformEEG: Towards Improving Model Generalizability in Deep Learning-based EEG Parkinson's Disease Detection
Federico Del Pup, Riccardo Brun, Filippo Iotti +7
Electroencephalography (EEG) is establishing itself as an important, low-cost, noninvasive diagnostic tool for the early detection of Parkinson's Disease (PD). In this context, EEG…
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…
xEEGNet: Towards Explainable AI in EEG Dementia Classification
Andrea Zanola, Louis Fabrice Tshimanga, Federico Del Pup +2
This work presents xEEGNet, a novel, compact, and explainable neural network for EEG data analysis. It is fully interpretable and reduces overfitting through major parameter reduct…