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ECCV
2006
Springer
16 years 8 months ago
Learning to Combine Bottom-Up and Top-Down Segmentation
Bottom-up segmentation based only on low-level cues is a notoriously difficult problem. This difficulty has lead to recent top-down segmentation algorithms that are based on class-...
Anat Levin, Yair Weiss
CHARME
2001
Springer
107views Hardware» more  CHARME 2001»
15 years 10 months ago
Using Combinatorial Optimization Methods for Quantification Scheduling
Model checking is the process of verifying whether a model of a concurrent system satisfies a specified temporal property. Symbolic algorithms based on Binary Decision Diagrams (BD...
Pankaj Chauhan, Edmund M. Clarke, Somesh Jha, Jame...
ESA
1998
Springer
108views Algorithms» more  ESA 1998»
15 years 11 months ago
Finding an Optimal Path without Growing the Tree
In this paper, we study a class of optimal path problems with the following phenomenon: The space complexity of the algorithms for reporting the lengths of single-source optimal pa...
Danny Z. Chen, Ovidiu Daescu, Xiaobo Hu, Jinhui Xu
JAMDS
2000
90views more  JAMDS 2000»
15 years 6 months ago
Stratified filtered sampling in stochastic optimization
We develop a methodology for evaluating a decision strategy generated by a stochastic optimization model. The methodology is based on a pilot study in which we estimate the distri...
Robert Rush, John M. Mulvey, John E. Mitchell, Tho...
ICASSP
2010
IEEE
15 years 4 months ago
GHT based implementation of the expectation maximization for mixtures of multi-Gaussians and its applications to video tracking
In this work, the problem of the estimation of parameters in case of mixtures of models composed by the sum of multiple Gaussians is considered. It will be shown how this estimati...
Francesco Monti, Carlo S. Regazzoni