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ISMB
1993
13 years 8 months ago
Using Dirichlet Mixture Priors to Derive Hidden Markov Models for Protein Families
A Bayesian method for estimating the amino acid distributions in the states of a hidden Markov model (HMM) for a protein familyor the columns of a multiple alignment of that famil...
Michael Brown, Richard Hughey, Anders Krogh, I. Sa...
ICMCS
2006
IEEE
139views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Automatic Semantic Annotation of Images using Spatial Hidden Markov Model
This paper presents a new spatial-HMM(SHMM)for automatically classifying and annotating natural images. Our model is a 2D generalization of the traditional HMM in the sense that b...
Feiyang Yu, Horace Ho-Shing Ip
IPCV
2010
13 years 5 months ago
Video Action Recognition Using Residual Vector Quantization and Hidden Markov Models
In this paper, we discuss usage of a multi-stage Residual Vector Quantization (RVQ) strategy for human action recognition. To the best of our knowledge, this is the first reported...
Salman Aslam, Christopher F. Barnes, Aaron F. Bobi...
BMCBI
2006
119views more  BMCBI 2006»
13 years 7 months ago
Hidden Markov Model Variants and their Application
Markov statistical methods may make it possible to develop an unsupervised learning process that can automatically identify genomic structure in prokaryotes in a comprehensive way...
Stephen Winters-Hilt
CSL
2010
Springer
13 years 7 months ago
The Hidden Information State model: A practical framework for POMDP-based spoken dialogue management
This paper explains how Partially Observable Markov Decision Processes (POMDPs) can provide a principled mathematical framework for modelling the inherent uncertainty in spoken di...
Steve Young, Milica Gasic, Simon Keizer, Fran&cced...