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TIP
2008
163views more  TIP 2008»
13 years 9 months ago
Image Modeling and Denoising With Orientation-Adapted Gaussian Scale Mixtures
We develop a statistical model to describe the spatially varying behavior of local neighborhoods of coefficients in a multiscale image representation. Neighborhoods are modeled as ...
David K. Hammond, Eero P. Simoncelli
TSP
2008
105views more  TSP 2008»
13 years 9 months ago
Semi-Supervised Linear Spectral Unmixing Using a Hierarchical Bayesian Model for Hyperspectral Imagery
This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linea...
Nicolas Dobigeon, Jean-Yves Tourneret, Chein-I Cha...
AMAI
1999
Springer
13 years 8 months ago
Pattern recognition by an optical thin-film multilayer model
This paper describes a computational learning model inspired by the technology of optical thin-film multilayers from the field of optics. With the thicknesses of thin-film layers ...
Xiaodong Li, Martin K. Purvis
NN
2002
Springer
224views Neural Networks» more  NN 2002»
13 years 8 months ago
Optimal design of regularization term and regularization parameter by subspace information criterion
The problem of designing the regularization term and regularization parameter for linear regression models is discussed. Previously, we derived an approximation to the generalizat...
Masashi Sugiyama, Hidemitsu Ogawa
CSDA
2010
100views more  CSDA 2010»
13 years 7 months ago
Least squares estimation of nonlinear spatial trends
The goal of this work is to study the asymptotic and finite sample properties of an estimator of a nonlinear regression function when errors are spatially correlated, and when the...
Rosa M. Crujeiras, Ingrid Van Keilegom