A multidimensional principal component analysis via the c-product Golub-Kahan-SVD for classification and face recognition.
Mustapha HachedKhalide JbilouChristos KoukouvinosMarilena MitrouliPublished in: CoRR (2021)
Keyphrases
- principal component analysis
- face recognition
- dimension reduction
- fisher linear discriminant
- singular value decomposition
- feature extraction
- discriminant analysis
- face images
- feature space
- dimensionality reduction
- linear discriminant analysis
- classification accuracy
- face databases
- low dimensional
- feature representation
- kernel principal component analysis
- recognition rate
- dimensionality reduction methods
- independent component analysis
- pattern recognition
- training set
- classification method
- support vector machine svm
- feature analysis
- covariance matrix
- life cycle
- image classification
- support vector
- text classification
- decision trees
- pattern classification
- principal components
- fisher criterion
- linear discriminate analysis
- singular values
- locality preserving projections
- class labels
- classification scheme
- classification models
- neural network
- training samples
- signal processing
- multi dimensional
- supervised learning
- computer vision