A computational model is presented for the detection of coherent motion based on template matching and hidden Markov models. The premise of this approach is that the growth in dete...
Background: Probabilistic models for sequence comparison (such as hidden Markov models and pair hidden Markov models for proteins and mRNAs, or their context-free grammar counterp...
Background: Baum-Welch training is an expectation-maximisation algorithm for training the emission and transition probabilities of hidden Markov models in a fully automated way. I...
We show some limitations of the ROUGE evaluation method for automatic summarization. We present a method for automatic summarization based on a Markov model of the source text. By...
This paper describes a technique for automatic recognition of off-line printed Arabic text using Hidden Markov Models. In this work different sizes of overlapping and non-overlapp...
Husni A. Al-Muhtaseb, Sabri A. Mahmoud, Rami Qahwa...
We present our studies on the application of Coupled Hidden Markov Models(CHMMs) to sports highlights extraction from broadcast video using both audio and video information. First,...
Hidden Markov Models (HMMs) provide a simple and effective framework for modelling time-varying spectral vector sequences. As a consequence, almost all present day large vocabula...
Motion trajectories provide rich spatio-temporal information about an object's activity. The trajectory information can be obtained using a tracking algorithm on data streams ...
Faisal I. Bashir, Ashfaq A. Khokhar, Dan Schonfeld
Hidden Markov Models, or HMMs for short, have been recently used in Bioinformatics for the classification of DNA or protein chains, giving rise to what is known as Profile Hidde...
Background: Identifying functional elements, such as transcriptional factor binding sites, is a fundamental step in reconstructing gene regulatory networks and remains a challengi...
Weichun Huang, David M. Umbach, Uwe Ohler, Leping ...