Kernel Low-Rank Entropic Component Analysis for Hyperspectral Image Classification.
Chengzu BaiRen ZhangZeshui XuBaogang JinJian ChenShuo ZhangLong-xia QianPublished in: IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. (2020)
Keyphrases
- component analysis
- low rank
- hyperspectral image classification
- matrix factorization
- factor analysis
- kernel matrix
- active learning
- linear combination
- hyperspectral
- missing data
- convex optimization
- hyperspectral images
- semi supervised
- singular value decomposition
- low rank matrix
- high dimensional data
- blind source separation
- high order
- collaborative filtering
- machine learning
- image data
- remote sensing
- negative matrix factorization
- recommender systems
- kernel pca
- feature space
- image segmentation