Towards Modality-Agnostic Seizure Classification: A Unified Deep Learning Framework for Heterogeneous EEG and Intracranial EEG Signals
A new framework of multimodal seizure classification integrating the heterogeneous EEG and iEEG recordings from different subjects and sources is presented, using the EEGNet-Vision Transformer as the feature extraction and classification network to learn the local discriminative patterns as well as global contextual in...
R. Sundaram, M. Jarwar, M. Uma et al.
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