In this paper, we propose a general two-dimensional hidden Markov model (2D-HMM), where dependency of the state transition probability on any state is allowed as long as causality...
Two Dimensional Hidden Markov Models (2D-HMMs) provide substantial benefits for many computer vision and image analysis applications. Many fundamental image analysis problems, inc...
Mehmet Emre Sargin, Alphan Altinok, Kenneth Rose, ...
In this paper, we propose a novel multi-dimensional distributed hidden Markov model (DHMM) framework. We first extend the theory of 2D hidden Markov models (HMMs) to arbitrary ca...
In this paper we present a variational Bayes (VB) framework for learning continuous hidden Markov models (CHMMs), and we examine the VB framework within active learning. Unlike a ...
Up-to-date results on the application of Markov models to chromosome analysis are presented. On the one hand, this means using continuous Hidden Markov Models (HMMs) instead of dis...