Multimodal Emotion Recognition: Emotion Classification Through the Integration of EEG and Facial Expressions by Songul Erdem Guler, Fatma Patlar Akbulut

“…The results validate the effectiveness of this approach, demonstrating the high accuracy of the Gated Recurrent Unit (GRU) model, which achieved an average of 91.8% classification accuracy on unimodal (EEG-only) data and an average of 97.8% classification accuracy on multimodal (EEG and facial expressions) datasets in the multi-class emotion categories. …”
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