Cargando…
EEG-based image classification via a region-level stacked bi-directional deep learning framework
BACKGROUND: As a physiological signal, EEG data cannot be subjectively changed or hidden. Compared with other physiological signals, EEG signals are directly related to human cortical activities with excellent temporal resolution. After the rapid development of machine learning and artificial intell...
Autores principales: | Fares, Ahmed, Zhong, Sheng-hua, Jiang, Jianmin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6921386/ https://www.ncbi.nlm.nih.gov/pubmed/31856818 http://dx.doi.org/10.1186/s12911-019-0967-9 |
Ejemplares similares
-
A deep learning framework using CNN and stacked Bi-GRU for COVID-19 predictions in India
por: Ahuja, Sahil, et al.
Publicado: (2021) -
EEG Classification of Motor Imagery Using a Novel Deep Learning Framework
por: Dai, Mengxi, et al.
Publicado: (2019) -
EEG-Based Emotion Classification Using Stacking Ensemble Approach
por: Chatterjee, Subhajit, et al.
Publicado: (2022) -
EEG Classification of Normal and Alcoholic by Deep Learning
por: Li, Houchi, et al.
Publicado: (2022) -
A Deep Transfer Learning Framework for Sleep Stage Classification with Single-Channel EEG Signals
por: ElMoaqet, Hisham, et al.
Publicado: (2022)