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» Higher order models for fuzzy random variables
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WSC
1997
13 years 9 months ago
Modeling Dependencies in Stochastic Simulation Inputs
We discuss some basic techniques for modeling dependence between the random variables that are inputs to a simulation model, with the main emphasis being continuous bivariate dist...
James R. Wilson
EMMCVPR
2011
Springer
12 years 7 months ago
Curvature Regularity for Multi-label Problems - Standard and Customized Linear Programming
Abstract. We follow recent work by Schoenemann et al. [25] for expressing curvature regularity as a linear program. While the original formulation focused on binary segmentation, w...
Thomas Schoenemann, Yubin Kuang, Fredrik Kahl
VLSM
2005
Springer
14 years 1 months ago
Uncertainty-Driven Non-parametric Knowledge-Based Segmentation: The Corpus Callosum Case
Abstract. In this paper we propose a novel variational technique for the knowledge based segmentation of two dimensional objects. One of the elements of our approach is the use of ...
Maxime Taron, Nikos Paragios, Marie-Pierre Jolly
MICCAI
2008
Springer
14 years 9 months ago
MR Brain Tissue Classification Using an Edge-Preserving Spatially Variant Bayesian Mixture Model
In this paper, a spatially constrained mixture model for the segmentation of MR brain images is presented. The novelty of this work is a new, edge preserving, smoothness prior whic...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. ...
FORTE
2004
13 years 9 months ago
Localizing Program Errors for Cimple Debugging
Abstract. We present automated techniques for the explanation of counterexamples, where a counter-example should be understood as a sequence of program statements. Our approach is ...
Samik Basu, Diptikalyan Saha, Scott A. Smolka