May 28, 2005 · We propose a formalism for deriving parametrised ensembles of local neighbourhood operators on the basis of a complete family of scale-space ...
Abstract. We propose a formalism for deriving parametrised ensembles of local neighbourhood operators on the basis of a complete family of scale-space.
Families of tuned scale-space kernels. Author: Florack, LMJ. ter Haar Romeny ... space kernel, each of which is tuned to a particular parameter value.
Families of Tuned Scale-Space Kernels. / Florack, Luc; Romeny, Bart M. ter Haar; Koenderink, Jan J. et al. ECCV. 1992. p. 19-23. ... AU - Koenderink, Jan J. ... AU ...
Families of Tuned Scale-Space Kernels. Authors: Luc Florack, Bart M. ter Haar ... Families of Tuned Scale-Space Kernels. Pages 19 - 23. PREVIOUS ARTICLE.
The goal of statistical scale space analysis is to extract scale-dependent features from noisy data. The data could be for example an observed time series or ...
Space-Time Kernels. In the statistics literature space-time kernels are more common. Stein uses kernels that are translation invariant in both space and time ...
As we have seen in Chapter 2, the use of kernel functions provides a powerful and principled way of detecting nonlinear relations using well-understood.
In machine learning, the kernel embedding of distributions (also called the kernel mean or mean map) comprises a class of nonparametric methods
This article studies sufficient conditions on families of approximating kernels which provide N-term approximation errors from an associated nonlinear ...
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