Ke-Xuan Zhu

MS-SSCTGN: a multi-scale self-supervised contrastive spatiotemporal network for EEG-based emotion recognition

Graph convolutional networks (GCNs), owing to their capability to effectively process non-Euclidean data, have become one of the dominant approaches for decoding emotional states from electroencephalography (EEG) signals. However, current brain region division strategies exhibit limitations in information extraction, a...