Electroencephalography based imagined alphabets classification using spatial and time-domain features.
Prabhakar AgarwalSandeep KumarPublished in: Int. J. Imaging Syst. Technol. (2022)
Keyphrases
- classification accuracy
- feature vectors
- feature set
- feature extraction
- eeg signals
- classification process
- classification method
- feature space
- spatial information
- eeg data
- irrelevant features
- classification models
- extracted features
- class labels
- extracting features
- discriminative features
- text classification
- svm classifier
- feature selection
- high dimensionality
- support vector
- support vector machine
- spatial distribution
- pattern recognition
- benchmark datasets
- decision tree classifiers
- features extraction
- classification rate
- feature values
- feature extraction and classification
- feature histograms
- decision trees
- image classification
- spatio temporal
- machine learning
- feature selection algorithms
- feature subset
- classification algorithm
- false positives
- frequency domain
- spatial relationships
- gender classification
- feature construction
- category labels
- training set
- low level
- image features
- signal processing
- support vector machine svm
- spatial and temporal
- spatial relations