Frontiers | hvEEGNet: a novel deep learning model for high-fidelity EEG reconstruction
1 Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy 2 Department of Information Engineering, University of Padova, Padova, Italy Introduction: Modeling multi-channel electroencephalographic (EEG) time-series is a challenging tasks, even for the most recent deep learning approaches. Particularly, in this work, we targeted our efforts to the high-fidelity reconstruction of this type of data, as this is of key relevance for several applications such as classifica