Cargando…
Emotion Recognition from Multiband EEG Signals Using CapsNet
Emotion recognition based on multi-channel electroencephalograph (EEG) signals is becoming increasingly attractive. However, the conventional methods ignore the spatial characteristics of EEG signals, which also contain salient information related to emotion states. In this paper, a deep learning fr...
Autores principales: | Chao, Hao, Dong, Liang, Liu, Yongli, Lu, Baoyun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6540345/ https://www.ncbi.nlm.nih.gov/pubmed/31086110 http://dx.doi.org/10.3390/s19092212 |
Ejemplares similares
-
DA-CapsNet: dual attention mechanism capsule network
por: Huang, Wenkai, et al.
Publicado: (2020) -
Efficient-CapsNet: capsule network with self-attention routing
por: Mazzia, Vittorio, et al.
Publicado: (2021) -
Prediction of Peptide Detectability Based on CapsNet and Convolutional Block Attention Module
por: Yu, Minzhe, et al.
Publicado: (2021) -
Multitask CapsNet: An Imbalanced Data Deep Learning
Method for Predicting Toxicants
por: Wang, Yiwei, et al.
Publicado: (2021) -
Intelligent Classification of Japonica Rice Growth Duration (GD) Based on CapsNets
por: Zhao, Xin, et al.
Publicado: (2022)