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...
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...
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...
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...
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...