1704 search results - page 66 / 341 » Learning nonlinear dynamic models |
156
Voted
Publication
We present a new approach for activity modelling and anomaly detection based on non-parametric Gaussian Process (GP) models. Specifically, GP regression models are formulated to l...
101
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GECCO
2007
Springer
15 years 6 months ago
2007
Springer
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
122
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ICASSP
2011
IEEE
14 years 4 months ago
2011
IEEE
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
115
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ICIP
2005
IEEE
16 years 2 months ago
2005
IEEE
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
ICCV
2009
IEEE
16 years 5 months ago
2009
IEEE
In this paper we describe a method to learn parameters
which govern pedestrian motion by observing video
data. Our learning framework is based on variational
mode learning and a...