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CVPR
2007
IEEE
14 years 9 months ago
Discriminative Learning of Dynamical Systems for Motion Tracking
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
Minyoung Kim, Vladimir Pavlovic
RECOMB
2003
Springer
14 years 7 months ago
Combining phylogenetic and hidden Markov models in biosequence analysis
A few models have appeared in recent years that consider not only the way substitutions occur through evolutionary history at each site of a genome, but also the way the process c...
Adam C. Siepel, David Haussler
PAMI
2008
189views more  PAMI 2008»
13 years 7 months ago
Detecting Objects of Variable Shape Structure With Hidden State Shape Models
This paper proposes a method for detecting object classes that exhibit variable shape structure in heavily cluttered images. The term "variable shape structure" is used t...
Jingbin Wang, Vassilis Athitsos, Stan Sclaroff, Ma...
ICIP
2007
IEEE
14 years 1 months ago
A General Two-Dimensional Hidden Markov Model and its Application in Image Classification
In this paper, we propose a general two-dimensional hidden Markov model (2D-HMM), where dependency of the state transition probability on any state is allowed as long as causality...
Xiang Ma, Dan Schonfeld, Ashfaq A. Khokhar
ICPR
2008
IEEE
14 years 1 months ago
Embedding HMM's-based models in a Euclidean space: The topological hidden Markov models
One of the major limitations of HMM-based models is the inability to cope with topology: When applied to a visible observation (VO) sequence, HMM-based techniques have difficulty ...
Djamel Bouchaffra