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» Reinforcement Learning State Estimator
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NIPS
1992
14 years 11 months ago
Hidden Markov Model} Induction by Bayesian Model Merging
This paper describes a technique for learning both the number of states and the topologyof Hidden Markov Models from examples. The inductionprocess starts with the most specific m...
Andreas Stolcke, Stephen M. Omohundro
PAMI
2010
205views more  PAMI 2010»
14 years 8 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille
IPMI
2005
Springer
15 years 10 months ago
Segmenting and Tracking the Left Ventricle by Learning the Dynamics in Cardiac Images
Having accurate left ventricle (LV) segmentations across a cardiac cycle provides useful quantitative (e.g. ejection fraction) and qualitative information for diagnosis of certain ...
Alan S. Willsky, Godtfred Holmvang, Müjdat &C...
ICML
2006
IEEE
15 years 10 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh
MLMI
2004
Springer
15 years 3 months ago
Emotion Analysis in Man-Machine Interaction Systems
Facial expression and hand gesture analysis plays a fundamental part in emotionally rich man-machine interaction (MMI) systems, since it employs universally accepted non-verbal cu...
T. Balomenos, Amaryllis Raouzaiou, Spiros Ioannou,...