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CVPR
2001
IEEE
14 years 9 months ago
A Bayesian Approach to Digital Matting
This paper proposes a new Bayesian framework for solving the matting problem, i.e. extracting a foreground element from a background image by estimating an opacity for each pixel ...
Yung-Yu Chuang, Brian Curless, David Salesin, Rich...
GECCO
2003
Springer
160views Optimization» more  GECCO 2003»
14 years 29 days ago
Hybridization of Estimation of Distribution Algorithms with a Repair Method for Solving Constraint Satisfaction Problems
Estimation of Distribution Algorithms (EDAs) are new promising methods in the field of genetic and evolutionary algorithms. In the case of conventional Genetic and Evolutionary Al...
Hisashi Handa
TIP
2010
127views more  TIP 2010»
13 years 6 months ago
Bayesian Compressive Sensing Using Laplace Priors
In this paper we model the components of the compressive sensing (CS) problem, i.e., the signal acquisition process, the unknown signal coefficients and the model parameters for ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
GECCO
2008
Springer
238views Optimization» more  GECCO 2008»
13 years 8 months ago
Using multiple offspring sampling to guide genetic algorithms to solve permutation problems
The correct choice of an evolutionary algorithm, a genetic representation for the problem being solved (as well as their associated variation operators) and the appropriate values...
Antonio LaTorre, José Manuel Peña, V...
WSC
2004
13 years 9 months ago
A Meta-Heuristic Based on Simulated Annealing for Solving Multiple-Objective Problems in Simulation Optimization
This paper presents a new meta heuristic algorithm based on the search method called simulated annealing, and its application to solving multi objective simulation optimization pr...
Eduardo Alberto Avello, Felipe F. Baesler, Reinald...