Dimensionality reduction in thermal tomography.
Jan HavelkaAnna KucerováJan SykoraPublished in: Comput. Math. Appl. (2019)
Keyphrases
- dimensionality reduction
- image reconstruction
- high dimensional
- high dimensional data
- principal component analysis
- data representation
- tomographic reconstruction
- low dimensional
- high dimensionality
- feature extraction
- feature space
- feature selection
- infrared
- pattern recognition
- random projections
- lower dimensional
- linear discriminant analysis
- data points
- singular value decomposition
- manifold learning
- dimensionality reduction methods
- structure preserving
- input space
- pattern recognition and machine learning
- nonlinear dimensionality reduction
- discrete tomography
- linear projection
- dimension reduction
- limited angle
- linear dimensionality reduction
- thermal images
- thermal imaging
- iterative reconstruction
- power plant
- locally linear embedding
- metric learning
- sparse representation
- heat transfer
- finite element analysis
- high temperature
- kernel pca
- kernel learning
- air conditioning
- super resolution
- view angles
- image processing