Quantum Dimension Reduction for Pattern Recognition in High-Resolution Spatio-Spectral Data.
Naveed MahmudBennett Haase-DivineAndrew MacGillivrayEsam El-ArabyPublished in: IEEE Trans. Computers (2022)
Keyphrases
- dimension reduction
- spectral data
- partial least squares
- pattern recognition
- high resolution
- feature extraction
- remote sensing
- image processing
- dimensionality reduction
- principal component analysis
- low resolution
- principal components
- low dimensional
- super resolution
- image analysis
- high dimensional
- linear discriminant analysis
- high dimensional data
- feature space
- neural network
- machine learning
- cluster analysis
- variable selection
- high quality
- random projections
- singular value decomposition
- hyperspectral
- principle component analysis
- computer vision
- feature selection
- multispectral
- semi supervised
- preprocessing
- satellite images
- unsupervised learning
- high dimensionality
- image segmentation
- hyperspectral images
- mass spectrometry