Discriminant Manifold Learning with Graph Convolution Based Regression for Image Classification.
Ruifeng ZhuFadi DornaikaYassine RuichekPublished in: GbRPR (2019)
Keyphrases
- manifold learning
- image classification
- feature extraction
- neighborhood graph
- low dimensional
- sparse representation
- locality preserving projections
- dimensionality reduction
- discriminant projection
- nonlinear dimensionality reduction
- high dimensional
- discriminant embedding
- graph embedding
- dimension reduction
- semi supervised
- principal component analysis
- image processing
- diffusion maps
- discriminant analysis
- subspace learning
- manifold structure
- random walk
- laplacian eigenmaps
- bag of words
- head pose estimation
- high dimensional data
- regression model
- image representation
- graph laplacian
- visual words
- support vector
- locality preserving
- preprocessing
- feature space
- linear discriminant analysis
- image features
- locally linear embedding
- pattern recognition
- feature vectors
- sparse coding
- support vector machine svm
- geodesic distance
- manifold embedding