Emotion recognition technology based on electroencephalogram (EEG) signals has become a focal point for experts and scholars globally. To improve the accuracy of machine understanding of human emotions, this paper characterizes the multidimensional information features in EEG signals, and solves the problem of 4-dimensional fusion of temporal, frequency and 2D spatial features of EEG signals, and we present a novel method named 4D-CapsBLnet. First, we transformed the multidimensional features from various channels into 4D structures for trainin...
