Randomized ICA and LDA Dimensionality Reduction Methods for Hyperspectral Image Classification.
Chippy JayaprakashBharath Bhushan DamodaranV. SowmyaK. P. SomanPublished in: CoRR (2018)
Keyphrases
- dimensionality reduction methods
- hyperspectral image classification
- principal component analysis
- independent component analysis
- linear discriminant analysis
- dimensionality reduction
- discriminant analysis
- face recognition
- active learning
- hyperspectral images
- hyperspectral
- feature extraction
- discriminant projection
- hyperspectral data
- principal components analysis
- random projections
- principle component analysis
- dimension reduction
- low dimensional
- independent components
- principal components
- high dimensional data
- signal processing
- preprocessing step
- machine learning
- feature space
- covariance matrix
- computer vision
- sparse representation
- pattern recognition
- feature selection
- high dimensional
- preprocessing
- high dimensionality
- hyperspectral imagery
- data points
- neural network
- kernel pca
- unsupervised learning
- support vector
- feature vectors
- image analysis
- image data
- remote sensing
- distance measure
- generative model