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Optimizing residual networks and vgg for classification of eeg signals: Identifying ideal channels for emotion recognition
Kit Hwa Cheah, Humaira Nisar
*
, Vooi Voon Yap,
Chen-Yi Lee
, G. R. Sinha
*
此作品的通信作者
神經調控醫療電子系統研究中心
電子研究所
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引文 斯高帕斯(Scopus)
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Keyphrases
Emotion Recognition
100%
Ideal Channel
100%
Residual Network
100%
ResNet18
100%
Image Processing
50%
EEG Signals
50%
Emotion Classification
50%
Human Health
25%
Optimal Performance
25%
Human Emotions
25%
Amygdala
25%
Classification Algorithms
25%
Publicly Available
25%
Sampling numbers
25%
Emotional Processing
25%
EEG Features
25%
Recognition Method
25%
Model Performance
25%
Brain Structure
25%
EEG Channels
25%
Neurofeedback
25%
Crucial Aspect
25%
EEG Database
25%
EEG Signal Processing
25%
Data Domain
25%
EEG Dataset
25%
Convolution Kernel
25%
Temporal Lobe
25%
Hierarchical Feature Extraction
25%
Health Recognition
25%
Shanghai Jiao Tong University
25%
Parameter Reduction
25%
Insular Cortex
25%
Kernel Dimension
25%
Anterior Pole
25%
Neuroscience
Image Processing
100%
Amygdala
50%
Temporal Lobe
50%
Insular Cortex
50%
Signal Processing
50%
Neurofeedback
50%
Computer Science
Residual Neural Network
100%
Image Processing
50%
Recognition System
25%
Optimal Performance
25%
Classification Algorithm
25%
Performance Model
25%
Brain Structure
25%
Data Domain
25%
Feature Extraction
25%