Electroencephalographic (EEG) based Deep Learning (DL): A Comparative Review
Deep learning (DL) has recently shown great promise in supporting knowledge of electroencephalographic (EEG) as a result of its ability to discover visual features (feature representation) from original (raw) data. This review will look at the latest developments in the research area of the EEG by...
Autores principales: | Riyadh Salam Mohammed, Ammar A. Al-Hamadani |
---|---|
Formato: | Artículo |
Lenguaje: | English |
Publicado: |
Al-Iraqia University - College of Engineering
2023-03-01
|
Colección: | Al-Iraqia Journal for Scientific Engineering Research |
Materias: | |
Acceso en línea: | https://ijser.aliraqia.edu.iq/index.php/ijser/article/view/59 |
Ejemplares similares
-
Automated Rest EEG-Based Diagnosis of Depression and Schizophrenia Using a Deep Convolutional Neural Network
por: Zhiming Wang, et al.
Publicado: (2022-01-01) -
A Systematic Review of Electroencephalography Open Datasets and Their Usage With Deep Learning Models
por: Alberto Nogales, et al.
Publicado: (2023-01-01) -
Emotion Detection from EEG Signals Using Machine Deep Learning Models
por: João Vitor Marques Rabelo Fernandes, et al.
Publicado: (2024-08-01) -
A Review on Artificial Intelligence methods and Signal Processing for EEG-Based lie and Truth Identification
por: Hamza Waleed Hamza, et al.
Publicado: (2024-06-01) -
Epileptic seizure detection with deep EEG features by convolutional neural network and shallow classifiers
por: Wei Zeng, et al.
Publicado: (2023-05-01)