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CVPR
2007
IEEE
15 years 12 months ago
Learning Gaussian Conditional Random Fields for Low-Level Vision
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
Marshall F. Tappen, Ce Liu, Edward H. Adelson, Wil...
ICPR
2004
IEEE
15 years 11 months ago
Gaussian Noise Elimination in Colour Images by Vector-Connected Filters
This paper deals with the use of vector-connected filters for eliminating Gaussian noise in colour images. This class of morphological filters suppresses noise but preserves the c...
Fernando Torres Medina, Francisco Ortiz, Pablo Gil
ICIP
2000
IEEE
15 years 2 months ago
Modelling Profiles with a Mixture of Gaussians
Point Distribution Models are useful tools for modelling the variability of particular classes of shapes. A common approach is to apply a Principle Component Analysis to the data,...
James Orwell, Darrel Greenhill, Jonathan D. Rymel,...
ICIP
2005
IEEE
15 years 3 months ago
Automatic registration of 3D datasets using Gaussian fields
—In this paper we introduce a new 3D automatic registration method based on Gaussian fields and energy minimization. The method defines a simple ∞ C energy function, which is c...
Faysal Boughorbel, Andreas Koschan, Mongi A. Abidi
ICA
2010
Springer
14 years 11 months ago
Use of Prior Knowledge in a Non-Gaussian Method for Learning Linear Structural Equation Models
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...
Takanori Inazumi, Shohei Shimizu, Takashi Washio