Evaluation of preference of multimedia content using deep neural networks for electroencephalography

Evaluation of quality of experience (Qo $E$) based on electroencephalography (EEG) has received great attention due to its capability of real-time Qo $E$ monitoring of users. However, it still suffers from rather low recognition accuracy. In this paper, we propose a novel method using deep neural networks toward improved modeling of EEG and thereby improved recognition accuracy. In particular, we aim to model spatio-temporal characteristics relevant for QoE analysis within learning models. The results demonstrate the effectiveness of the proposed method.