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 ...
Abstract--Generative models are created to be used in the design and performance assessment of high layer wireless communication protocols and some error control strategies. Genera...
Omar S. Salih, Cheng-Xiang Wang, David I. Laurenso...
In this paper, we study unsupervised image segmentation using wavelet-domain hidden Markov models (HMMs). We first review recent supervised Bayesian image segmentation algorithms ...
This paper proposes some Markov Random Field (MRF) models for restoration of stereo disparity maps. The main aspect is the use of confidence maps provided by the Symmetric Multipl...
Andrea Fusiello, Umberto Castellani, Vittorio Muri...
We present a semi-Markov model for recognizing scene text that integrates character and word segmentation with recognition. Using wavelet features, it requires only approximate lo...
Allen R. Hanson, Erik G. Learned-Miller, Jerod J. ...