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22.214  Articles
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Modeling background and segmenting moving objects are significant techniques for video surveillance and other video processing applications. In this paper, we proposed a novel adaptive approach modeling background and segmenting moving object with non-par... see more

Ad hoc methods in the choice of smoothing parameter in kernel density estimation, al­though often used in practice due to their simplicity and hence the calculated efficiency, are char­acterized by quite big error. The value of the smoothing parameter cho... see more

This paper studies probability density estimation on the Siegel space. The Siegel space is a generalization of the hyperbolic space. Its Riemannian metric provides an interesting structure to the Toeplitz block Toeplitz matrices that appear in the covaria... see more

The relationship between a current observation and previous observations, where the conditional density function plays an important role, is the main subject of this paper. To study this relation, the unknown conditional density function must be estimated... see more

The relationship between a current observation and previous observations, where the conditional density function plays an important role, is the main subject of this paper. To study this relation, the unknown conditional density function must be estimated... see more

The urban facility, one of the most important service providers is usuallyrepresented by sets of points in GIS applications using POI (Point of Interest) modelassociated with certain human social activities. The knowledge about distributionintensity and p... see more

One of the fundamental data analytics tools in statistical estimation is the non-parametric kernel method that involves probability estimates production. The method uses the observations to obtain useful statistical information to aid the practicing stati... see more

One of the fundamental data analytics tools in statistical estimation is the non-parametric kernel method that involves probability estimates production. The method uses the observations to obtain useful statistical information to aid the practicing stati... see more

Trend renewal process (TRP) is a generalized stochastic point processwith two elements of a nonhomogeneous Poisson process (NHPP) and a renewal process (RP), and plays a significant role to represent a sub-class of general repair models. Nonparametric est... see more

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