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PAMI
2007
123views more  PAMI 2007»
13 years 10 months ago
Unsupervised Statistical Segmentation of Nonstationary Images Using Triplet Markov Fields
—Recent developments in statistical theory and associated computational techniques have opened new avenues for image modeling as well as for image segmentation techniques. Thus, ...
Dalila Benboudjema, Wojciech Pieczynski
CORR
2010
Springer
162views Education» more  CORR 2010»
13 years 11 months ago
Random sampling of lattice paths with constraints, via transportation
We investigate Monte Carlo Markov Chain (MCMC) procedures for the random sampling of some one-dimensional lattice paths with constraints, for various constraints. We will see that...
Lucas Gerin
PAMI
2008
119views more  PAMI 2008»
13 years 11 months ago
Triplet Markov Fields for the Classification of Complex Structure Data
We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
Juliette Blanchet, Florence Forbes
DAGM
2008
Springer
14 years 23 days ago
Approximate Parameter Learning in Conditional Random Fields: An Empirical Investigation
We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...
Filip Korc, Wolfgang Förstner
ECML
2006
Springer
14 years 2 months ago
TildeCRF: Conditional Random Fields for Logical Sequences
Abstract. Conditional Random Fields (CRFs) provide a powerful instrument for labeling sequences. So far, however, CRFs have only been considered for labeling sequences over flat al...
Bernd Gutmann, Kristian Kersting