(Semi-) Supervised Mixtures of Factor Analyzers and Deep Mixtures of Factor Analyzers Dimensionality Reduction Algorithms For Hyperspectral Images Classification.
Bin ZhaoJohannes R. SveinssonMagnus O. UlfarssonJocelyn ChanussotPublished in: IGARSS (2019)
Keyphrases
- factor analyzers
- low dimensional
- hyperspectral images
- dimensionality reduction
- hyperspectral data
- pattern recognition
- semi supervised
- dimensionality reduction methods
- dimension reduction
- feature space
- high dimensional
- feature vectors
- learning algorithm
- high dimensionality
- unsupervised learning
- data points
- feature extraction
- hyperspectral
- kernel learning
- principal component analysis
- hyperspectral imagery
- feature selection
- image processing
- machine learning
- mutual information
- hyperspectral image classification
- computer vision
- random projections
- principal components
- remote sensing
- high dimensional data
- semi supervised learning
- labeled data