Large-Scale Feature Selection With Gaussian Mixture Models for the Classification of High Dimensional Remote Sensing Images.
Adrien LagrangeMathieu FauvelManuel GrizonnetPublished in: IEEE Trans. Computational Imaging (2017)
Keyphrases
- gaussian mixture model
- remote sensing images
- feature selection
- feature space
- high dimensional
- high dimensionality
- classification accuracy
- feature vectors
- mixture model
- change detection
- remote sensing
- multi spectral images
- landsat etm
- multispectral
- text classification
- density estimation
- feature extraction
- spectral features
- support vector
- unsupervised learning
- feature set
- dimensionality reduction
- satellite images
- machine learning
- maximum likelihood
- pattern recognition
- model selection
- class labels
- probability density function
- speaker recognition
- maximum likelihood criterion
- high quality
- decision trees
- em algorithm
- low dimensional
- supervised learning
- information retrieval
- clustering algorithm
- neural network
- marked point processes
- land cover
- supervised classification
- pattern classification
- high resolution
- data points
- image registration
- principal component analysis
- data sets