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...
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...
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...
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 ...
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...