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ECCV
1994
Springer
13 years 11 months ago
Markov Random Field Models in Computer Vision
A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is dened as the maximum a posteriori (MAP) probability estimate...
Stan Z. Li
ICN
2007
Springer
14 years 1 months ago
Heuristic Approach of Optimal Code Allocation in High Speed Downlink Packet Access Networks
— In this paper, we use the Markov Decision Process (MDP) technique to find the optimal code allocation policy in High-Speed Downlink Packet Access (HSDPA) networks. A discrete ...
Hussein Al-Zubaidy, Jerome Talim, Ioannis Lambadar...
ICDAR
2003
IEEE
14 years 1 months ago
Optimizing the Number of States, Training Iterations and Gaussians in an HMM-based Handwritten Word Recognizer
In off-line handwriting recognition, classifiers based on hidden Markov models (HMMs) have become very popular. However, while there exist well-established training algorithms, s...
Simon Günter, Horst Bunke
ICDAR
2011
IEEE
12 years 7 months ago
On-line Handwritten Japanese Characters Recognition Using a MRF Model with Parameter Optimization by CRF
— This paper describes a Markov random field (MRF) model with weighting parameters optimized by conditional random field (CRF) for on-line recognition of handwritten Japanese cha...
Bilan Zhu, Masaki Nakagawa
AAAI
1997
13 years 9 months ago
Model Minimization in Markov Decision Processes
Many stochastic planning problems can be represented using Markov Decision Processes (MDPs). A difficulty with using these MDP representations is that the common algorithms for so...
Thomas Dean, Robert Givan