Implicit Regression in Subspace for High-Sensitivity CEST Imaging.
Chu ChenYang LiuSe Weon ParkJizhou LiKannie W. Y. ChanRaymond H. F. ChanPublished in: CoRR (2024)
Keyphrases
- high sensitivity
- regression model
- optical fiber
- low dimensional
- image processing
- subspace clustering
- imaging systems
- medical imaging
- image analysis
- high resolution
- model selection
- regression problems
- kernel based nonlinear
- principal component analysis
- regression analysis
- high dimensional data
- linear subspace
- gaussian processes
- subspace learning
- feature extraction
- polynomial regression
- linear regression
- dimensionality reduction
- regression methods
- regression function
- imaging devices
- acquired images
- lower dimensional
- support vector regression
- input data
- feature space
- support vector
- atomic force microscopy
- data sets
- fiber bragg grating
- ridge regression
- regression algorithm
- subspace methods
- clinical applications
- nearest neighbor
- high dimensional
- computer vision