Before revision: To overcome these challenges, in this paper, we present a deep learning based framework which uses a Convolutional Neural Network (CNN) with dense connections and learns highly robust features at different spatial and temporal resolutions of the EEG data spectrum for accurate cross-patient seizure type classification.
After revision: To overcome these challenges, in this paper, we present a deep learning based framework which learns multi-spectralfeature embeddings using multiple CNN models in an ensem-ble architecture for accurate cross-patient seizure type classification.