Dimensionality Reduction Using Discriminative Autoencoders for Remote Sensing Image Retrieval.
MohbatTooba MukhtarNuman KhurshidMurtaza TajPublished in: ICIAP (1) (2019)
Keyphrases
- remote sensing
- dimensionality reduction
- image retrieval
- feature extraction
- unsupervised learning
- change detection
- feature selection
- image processing
- high resolution
- multispectral
- feature space
- denoising
- image analysis
- remote sensing imagery
- remote sensing images
- pattern recognition
- high dimensional data
- principal component analysis
- satellite images
- hyperspectral
- image fusion
- satellite data
- satellite imagery
- high dimensional
- low dimensional
- automatic image registration
- remote sensing data
- land cover
- image content
- remotely sensed images
- high spatial resolution
- principal components
- linear discriminant analysis
- random projections
- hyperspectral imagery
- image representation
- remotely sensed
- hyperspectral images
- remote sensed images
- multi spectral images
- earth observation
- data points
- semi supervised
- sparse representation
- digital image analysis
- remotely sensed imagery
- hyperspectral remote sensing
- earth science
- dimension reduction
- remotely sensed data
- high quality
- supervised classification