LION
2009
Springer
13 years 10 months ago
2009
Springer
A very undesirable behavior of any heuristic algorithm is to be stuck in some specific parts of the search space, in particular in the basins of attraction of the local optima. Wh...
LION
2009
Springer
13 years 10 months ago
2009
Springer
Abstract. Probabilistic Neural Networks (PNNs) constitute a promising methodology for classification and prediction tasks. Their performance depends heavily on several factors, su...
ICPR
2010
IEEE
13 years 11 months ago
2010
IEEE
Many vision applications have been formulated as Markov Random Field (MRF) problems. Although many of them are discrete labeling problems, continuous formulation often achieves gre...
ECCV
2008
Springer
14 years 2 months ago
2008
Springer
There are many local and greedy algorithms for energy minimization over Markov Random Field (MRF) such as iterated condition mode (ICM) and various gradient descent methods. Local ...
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CVPR
2009
IEEE
14 years 11 months ago
2009
IEEE
In this paper, we introduce a higher-order MRF optimization
framework. On the one hand, it is very general;
we thus use it to derive a generic optimizer that can be applied
to a...
Source Code
A library for developing portable applications that deal with networking, threads (message passing, futures, etc...), graphical interfaces, complex data structures, linear algebra,...
Source Code
A C++ program that utilizes the quick and accurate implementation of the simplex method (i.e., unconstrained nonlinear optimization) using vtk 4.2.