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A Deep Learning MI - EEG Classification Model for BCIs
Hauke Dose, Jakob S. Moller, Sadasivan Puthusserypady,
Helle K. Iversen
Institut for Klinisk Medicin
12
Citationer (Scopus)
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Keyphrases
Convolutional Neural Network Model
50%
Electroencephalogram Classification
100%
Electroencephalogram Data
50%
End-to-end Convolutional Neural Network
50%
MI-EEG
100%
Motor Imagery Training
50%
Raw Electroencephalogram
50%
Raw Signal
50%
Spatial Convolution
50%
Temporal Convolutional Network
50%
Engineering
Brain-Computer Interface
100%
Classification Method
25%
Convolutional Neural Network
25%
Deep Learning Method
100%
Feature Extraction
25%
Learning Approach
25%
Limited Number
25%
Motor Imagery
100%
Network Model
25%
State-of-the-Art Method
25%
Computer Science
Classification Method
25%
Classification Models
100%
Computer Interface
25%
Convolutional Neural Network
25%
Deep Learning Method
100%
Feature Extraction
25%
Fully Connected Layer
25%
Learning Approach
25%
Neural Network Model
25%
Preprocessing
25%
Reported Result
25%
Single Individual
25%
Earth and Planetary Sciences
Pattern Recognition
100%
Preprocessing
100%
State of the Art
100%
Chemical Engineering
Deep Learning Method
100%
Neural Network
25%