Abstract:Emotion recognition from EEG signals is a major field of research in cognitive computing. The major challenges involved in the task are extracting meaningful features from the signals and building an accurate model. This paper proposes a fuzzy ensemble-based deep learning approach to classify emotions from EEG-based models. Three individual deep learning models have been trained and combined using a fuzzy rank-based approach implemented using the Gompertz function. The model has been tested on two benchmark da… Show more
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