Cargando…
Electroencephalogram Access for Emotion Recognition Based on a Deep Hybrid Network
In the human-computer interaction (HCI), electroencephalogram (EEG) access for automatic emotion recognition is an effective way for robot brains to perceive human behavior. In order to improve the accuracy of the emotion recognition, a method of EEG access for emotion recognition based on a deep hy...
Autores principales: | Zhong, Qinghua, Zhu, Yongsheng, Cai, Dongli, Xiao, Luwei, Zhang, Han |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7772146/ https://www.ncbi.nlm.nih.gov/pubmed/33390918 http://dx.doi.org/10.3389/fnhum.2020.589001 |
Ejemplares similares
-
Enhancing the accuracy of electroencephalogram-based emotion recognition through Long Short-Term Memory recurrent deep neural networks
por: Yousefi, Mohammad Reza, et al.
Publicado: (2023) -
Multifractal Functional Connectivity Analysis of Electroencephalogram Reveals Reorganization of Brain Networks in a Visual Pattern Recognition Paradigm
por: Stylianou, Orestis, et al.
Publicado: (2021) -
Hybrid transfer learning strategy for cross-subject EEG emotion recognition
por: Lu, Wei, et al.
Publicado: (2023) -
The multiscale 3D convolutional network for emotion recognition based on electroencephalogram
por: Su, Yun, et al.
Publicado: (2022) -
Effects of deep brain stimulation on quantitative sleep electroencephalogram during non-rapid eye movement in Parkinson’s disease
por: Memon, Adeel A., et al.
Publicado: (2023)