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What is AE-CDNN for EEG Feature Learning about?

This document discusses using deep learning models for unsupervised feature learning from EEG signals to help detect and classify epilepsy. It proposes an autoencoding framework called AE-CDNN that combines convolution and deconvolution networks to learn low-dimensional features from high-dimensional EEG data in an unsupervised manner. Experimental results on public EEG datasets show that features extracted by AE-CDNN achieve high accuracy for epilepsy classification, comparable or better than other recent

Author

investigacion

Language

EN