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ICPR
2010
IEEE
15 years 4 months ago
Continuous Markov Random Field Optimization using Fusion Move Driven Markov Chain Monte Carlo Technique
Many vision applications have been formulated as Markov Random Field (MRF) problems. Although many of them are discrete labeling problems, continuous formulation often achieves gre...
Wonsik Kim (Seoul National University), Kyoung Mu ...
PERCOM
2009
ACM
15 years 4 months ago
Markov Chain Existence and Hidden Markov Models in Spectrum Sensing
—The primary function of a cognitive radio is to detect idle frequencies or sub-bands, not used by the primary users (PUs), and allocate these frequencies to secondary users. The...
Chittabrata Ghosh, Carlos de M. Cordeiro, Dharma P...
77
Voted
CSDA
2007
116views more  CSDA 2007»
14 years 9 months ago
Exploring the state sequence space for hidden Markov and semi-Markov chains
The knowledge of the state sequences that explain a given observed sequence for a known hidden Markovian model is the basis of various methods that may be divided into three categ...
Yann Guédon
CVPR
2009
IEEE
15 years 7 months ago
Markov Chain Monte Carlo Combined with Deterministic Methods for Markov Random Field Optimization
Many vision problems have been formulated as en- ergy minimization problems and there have been signif- icant advances in energy minimization algorithms. The most widely-used energ...
Wonsik Kim (Seoul National University), Kyoung Mu ...
JSC
2006
56views more  JSC 2006»
14 years 9 months ago
Viterbi sequences and polytopes
A Viterbi path of length n of a discrete Markov chain is a sequence of n + 1 states that has the greatest probability of ocurring in the Markov chain. We divide the space of all M...
Eric H. Kuo