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» Higher order models for fuzzy random variables
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WSC
1997
14 years 11 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
13 years 9 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
15 years 3 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
15 years 10 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
14 years 11 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