Spatially aware supervised nonlinear dimensionality reduction for hyperspectral data.
Michele VolpiDevis TuiaPublished in: WHISPERS (2014)
Keyphrases
- nonlinear dimensionality reduction
- hyperspectral data
- spatially aware
- hyperspectral
- random projections
- hyperspectral images
- hyperspectral imagery
- dimensionality reduction
- manifold learning
- low dimensional
- multispectral
- remote sensing
- semi supervised
- high dimensional data
- dimensionality reduction methods
- infrared
- supervised learning
- learning algorithm
- dimension reduction
- unsupervised learning
- high dimensional
- feature selection
- principal components
- locally linear embedding
- feature extraction
- riemannian manifolds
- linear discriminant analysis
- pattern recognition
- data analysis
- sparse representation
- random sampling
- high dimensionality
- image processing
- data sets
- principal component analysis