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INFORMATICALT
2006
150views more  INFORMATICALT 2006»
13 years 10 months ago
A Multiresolution Approach Based on MRF and Bak-Sneppen Models for Image Segmentation
The two major Markov Random Fields (MRF) based algorithms for image segmentation are the Simulated Annealing (SA) and Iterated Conditional Modes (ICM). In practice, compared to the...
Kamal E. Melkemi, Mohamed Batouche, Sebti Foufou
BMCBI
2007
160views more  BMCBI 2007»
13 years 10 months ago
Identifying protein complexes directly from high-throughput TAP data with Markov random fields
Background: Predicting protein complexes from experimental data remains a challenge due to limited resolution and stochastic errors of high-throughput methods. Current algorithms ...
Wasinee Rungsarityotin, Roland Krause, Arno Sch&ou...
ICIP
2003
IEEE
14 years 11 months ago
A probabilistic framework for image segmentation
A new probabilistic image segmentation model based on hypothesis testing and Gibbs Random Fields is introduced. First, a probabilistic difference measure derived from a set of hyp...
Slawo Wesolkowski, Paul W. Fieguth
NIPS
2008
13 years 11 months ago
Multiscale Random Fields with Application to Contour Grouping
We introduce a new interpretation of multiscale random fields (MSRFs) that admits efficient optimization in the framework of regular (single level) random fields (RFs). It is base...
Longin Jan Latecki, ChengEn Lu, Marc Sobel, Xiang ...
ICCV
2009
IEEE
1048views Computer Vision» more  ICCV 2009»
15 years 3 months ago
Face Recognition With Contiguous Occlusion Using Markov Random Fields
Partially occluded faces are common in many applications of face recognition. While algorithms based on sparse representation have demonstrated promising results, they achieve t...
Zihan Zhou, Andrew Wagner, Hossein Mobahi, John Wr...