Comparing the Performance of Principal Component Analysis and RBF Network for Face Recognition using Locally Linear Embedding.
Eimad Eldin AbushamDavid Ngo Chek LingAndrew Teoh Beng JinPublished in: IASSE (2005)
Keyphrases
- rbf network
- locally linear embedding
- principal component analysis
- dimensionality reduction
- face images
- low dimensional
- radial basis function
- manifold learning
- high dimensional data
- high dimensional
- rbf neural network
- nonlinear functions
- dimensionality reduction methods
- subspace learning
- dimension reduction
- back propagation
- hidden units
- covariance matrix
- input space
- dimensional data
- feature extraction
- face recognition
- multilayer perceptron
- triangular mesh
- learning algorithm
- principal components
- discriminant analysis
- pattern recognition
- linear discriminant analysis
- learning tasks
- training algorithm
- unsupervised learning
- random projections
- feature space
- image processing
- neural network
- sparse representation
- geodesic distance
- image classification
- data points
- training data