115 search results - page 3 / 23 » Constraints and Application Conditions: From Graphs to High-... |
AUSAI
2005
Springer
14 years 1 months ago
2005
Springer
Abstract. Programmers employing inference in Bayesian networks typically rely on the inclusion of the model as well as an inference engine into their application. Sophisticated inf...
CVPR
2010
IEEE
14 years 3 months ago
2010
IEEE
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
UAI
2004
13 years 8 months ago
2004
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property ...
ECCV
2002
Springer
14 years 9 months ago
2002
Springer
In this paper, the geometry of a general class of projections from ??? to ?! is examined, as a generalization of classic multiple view geometry in computer vision. It is shown that...
HIPS
1998
IEEE
13 years 11 months ago
1998
IEEE
Industrial applications use specific problem-oriented implementations of large sparse and irregular data structures. Hence there is a need for tools that make it possible for deve...