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ICML
2006
IEEE
14 years 8 months ago
Null space versus orthogonal linear discriminant analysis
Dimensionality reduction is an important pre-processing step for many applications. Linear Discriminant Analysis (LDA) is one of the well known methods for supervised dimensionali...
Jieping Ye, Tao Xiong
ICIP
2000
IEEE
14 years 9 months ago
Model-Based Inverse Halftoning with Wavelet-Vaguelette Deconvolution
In this paper, we demonstrate based on the linear model of [1, 2] that inverse halftoning is equivalent to the well-studied problem of deconvolution in the presence of colored noi...
Ramesh Neelamani, Robert Nowak, Richard G. Baraniu...
ACII
2005
Springer
13 years 9 months ago
A Novel Regularized Fisher Discriminant Method for Face Recognition Based on Subspace and Rank Lifting Scheme
The null space N(St) of total scatter matrix St contains no useful information for pattern classification. So, discarding the null space N(St) results in dimensionality reduction ...
Wen-Sheng Chen, Pong Chi Yuen, Jian Huang, Jian-Hu...
ISBI
2006
IEEE
14 years 8 months ago
Reconstruction of undersampled dynamic spiral MR images
The temporal resolution of dynamic MRI can be increased by sampling a fraction of k-space in an interleaved fashion, which causes spatial and temporal aliasing. We describe algebr...
Taehoon Shin, Jon F. Nielsen, Krishna S. Nayak
PR
2008
129views more  PR 2008»
13 years 7 months ago
A comparison of generalized linear discriminant analysis algorithms
7 Linear discriminant analysis (LDA) is a dimension reduction method which finds an optimal linear transformation that maximizes the class separability. However, in undersampled p...
Cheong Hee Park, Haesun Park