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» Gaussian Process Models of Spatial Aggregation Algorithms
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PAMI
2008
140views more  PAMI 2008»
13 years 7 months ago
Simplifying Mixture Models Using the Unscented Transform
Mixture of Gaussians (MoG) model is a useful tool in statistical learning. In many learning processes that are based on mixture models, computational requirements are very demandin...
Jacob Goldberger, Hayit Greenspan, Jeremie Dreyfus...
IJIT
2004
13 years 9 months ago
Evaluation of Algorithms for Sequential Decision in Biosonar Target Classification
A sequential decision problem, based on the task of identifying the species of trees given acoustic echo data collected from them, is considered with well-known stochastic classifi...
Turgay Temel, John Hallam
ADBIS
2000
Springer
91views Database» more  ADBIS 2000»
13 years 11 months ago
Efficient Region Query Processing by Optimal Page Ordering
A number of algorithms of clustering spatial data for reducing the number of disk seeks required to process spatial queries have been developed. One of the algorithms is the scheme...
Daesoo Cho, Bonghee Hong
CVPR
2008
IEEE
14 years 9 months ago
Edge preserving spatially varying mixtures for image segmentation
A new hierarchical Bayesian model is proposed for image segmentation based on Gaussian mixture models (GMM) with a prior enforcing spatial smoothness. According to this prior, the...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. Ga...
IJCV
2008
188views more  IJCV 2008»
13 years 7 months ago
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
Elise Arnaud, Étienne Mémin