Sparse two-dimensional discriminant locality-preserving projection (S2DDLPP) for feature extraction.
Minghua WanGuowei YangChengli SunMaoxi LiuPublished in: Soft Comput. (2019)
Keyphrases
- locality preserving projections
- feature extraction
- face recognition
- dimensionality reduction
- linear discriminant analysis
- manifold learning
- principal component analysis
- sparse coding
- sparse representation
- locality preserving
- high dimensional
- random projections
- discriminant analysis
- image classification
- dimension reduction
- feature space
- subspace learning
- low dimensional
- feature vectors
- subspace methods
- image processing
- pattern recognition
- recognition rate
- texture classification
- support vector machine svm
- high dimensional data
- locally linear embedding
- multi dimensional
- support vector
- machine learning
- independent component analysis
- unsupervised learning
- natural images
- data representation
- principal components analysis
- canonical correlation analysis
- discriminative information
- principle component analysis
- texture analysis
- texture features
- feature selection