Manifold learning using Euclidean k-nearest neighbor graphs [image processing examples].
Jose A. CostaAlfred O. Hero IIIPublished in: ICASSP (3) (2004)
Keyphrases
- manifold learning
- k nearest neighbor
- neighborhood graph
- knn
- graph construction
- image processing
- nearest neighbor
- dimensionality reduction
- low dimensional
- feature extraction
- semi supervised
- high dimensional
- nonlinear dimensionality reduction
- high dimensional data
- subspace learning
- dimension reduction
- support vector machine
- pattern recognition
- euclidean space
- laplacian eigenmaps
- support vector machine svm
- euclidean distance
- text classification
- knn classifier
- sparse representation
- manifold structure
- signal processing
- feature space
- neural network
- data points
- multiscale
- graph laplacian
- feature mapping
- locally linear embedding
- riemannian manifolds
- input space
- range queries
- image segmentation
- feature selection
- computer vision
- machine learning