Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classificati...
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
This paper presents a Hidden Markov Mesh Random Field (HMMRF) based approach for off-line handwritten Chinese characters recognition using statistical observation sequences embedd...
Qing Wang, Rongchun Zhao, Zheru Chi, David Dagan F...
Markov Random Fields (MRF's) can be used for a wide variety of vision problems. In this paper we focus on MRF's with two-valued clique potentials, which form a generaliz...
In this paper, we study the optimal way of distributing sensors in a random field to minimize the estimation distortion. We show that this problem is equivalent to certain proble...