Cargando…
Emotion Recognition from Physiological Channels Using Graph Neural Network
In recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work...
Autores principales: | Wierciński, Tomasz, Rock, Mateusz, Zwierzycki, Robert, Zawadzka, Teresa, Zawadzki, Michał |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9025566/ https://www.ncbi.nlm.nih.gov/pubmed/35458965 http://dx.doi.org/10.3390/s22082980 |
Ejemplares similares
-
Graph Representation Integrating Signals for Emotion Recognition and Analysis
por: Zawadzka, Teresa, et al.
Publicado: (2021) -
Multi-channel EEG emotion recognition through residual graph attention neural network
por: Chao, Hao, et al.
Publicado: (2023) -
Cross-Subject EEG Emotion Recognition With Self-Organized Graph Neural Network
por: Li, Jingcong, et al.
Publicado: (2021) -
CR-GCN: Channel-Relationships-Based Graph Convolutional Network for EEG Emotion Recognition
por: Jia, Jingjing, et al.
Publicado: (2022) -
Sparse Spatial-Temporal Emotion Graph Convolutional Network for Video Emotion Recognition
por: Liu, Xiaodong, et al.
Publicado: (2022)