EEG-based emotion classification using deep belief networks

Abstract

In recent years, there are many great successes in using deep architectures for unsupervised feature learning from data, especially for images and speech. In this paper, we introduce recent advanced deep learning models to classify two emotional categories (positive and negative) from EEG data. We train a deep belief network (DBN) with differential entropy… (More)
DOI: 10.1109/ICME.2014.6890166

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