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IEEECGIV
2009
IEEE
16 years 1 months ago
Two Dimensional Compressive Classifier for Sparse Images
The theory of compressive sampling involves making random linear projections of a signal. Provided signal is sparse in some basis, small number of such measurements preserves the ...
Armin Eftekhari, Hamid Abrishami Moghaddam, Massou...
ICIP
2006
IEEE
16 years 13 days ago
Compressive Sampling Vs. Conventional Imaging
Compressive sampling (CS), or “Compressed Sensing,” has recently generated a tremendous amount of excitement in the image processing community. CS involves taking a relatively...
Jarvis Haupt, Robert Nowak
ICDM
2010
IEEE
164views Data Mining» more  ICDM 2010»
15 years 4 months ago
Improved Consistent Sampling, Weighted Minhash and L1 Sketching
Abstract--We propose a new Consistent Weighted Sampling method, where the probability of drawing identical samples for a pair of inputs is equal to their Jaccard similarity. Our me...
Sergey Ioffe
IGARSS
2009
15 years 4 months ago
Classification Performance of Random-projection-based Dimensionality Reduction of Hyperspectral Imagery
High-dimensional data such as hyperspectral imagery is traditionally acquired in full dimensionality before being reduced in dimension prior to processing. Conventional dimensiona...
James E. Fowler, Qian Du, Wei Zhu, Nicolas H. Youn...
ICCV
2003
IEEE
16 years 8 months ago
Catadioptric Camera Calibration Using Geometric Invariants
Central catadioptric cameras are imaging devices that use mirrors to enhance the field of view while preserving a single effective viewpoint. In this paper, we propose a novel met...
Xianghua Ying, Zhanyi Hu