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Propositional systems, Hilbert lattices and generalized Hilbert spaces
, 2006
"... Abstract. With this chapter we provide a compact yet complete survey of two most remarkable “representation theorems”: every arguesian projective geometry is represented by an essentially unique vector space, and every arguesian Hilbert geometry is represented by an essentially unique generalized Hi ..."
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Cited by 9 (0 self)
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Abstract. With this chapter we provide a compact yet complete survey of two most remarkable “representation theorems”: every arguesian projective geometry is represented by an essentially unique vector space, and every arguesian Hilbert geometry is represented by an essentially unique generalized
A General Hilbert Space Approach to Wavelets and Its Application in Geopotential Determination
, 1999
"... A general approach to wavelets is presented within a framework of a separable functional Hilbert space H. Basic tool is the construction of Hproduct kernels by use of Fourier analysis with respect to an orthonormal basis in H. Scaling function and wavelet are defined in terms of Hproduct kernels. ..."
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Cited by 2 (0 self)
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A general approach to wavelets is presented within a framework of a separable functional Hilbert space H. Basic tool is the construction of Hproduct kernels by use of Fourier analysis with respect to an orthonormal basis in H. Scaling function and wavelet are defined in terms of Hproduct kernels
A GENERAL HILBERT SPACE FRAMEWORK FOR THE DlSCRETlZATlON OF CONTINUOUS SIGNAL PROCESSING OPERATORS
"... We present a unifying framework for the design of discrete algorithms that implement continuous signal processing operators. The underlying continuoustime signals are represented as linear combinations of the integershifts of a generating function cpi with (i=1,2) (continuous/discrete representati ..."
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/discrete representation). The corresponding input and output functions spaces are V(cp,) and V(cp,), respectively. The principle of the method is as follows: we start by interpolating the discrete input signal with a function s, E V(cp,). We then apply a linear operator T to this function and compute the minimum error
The irreducibility of the space of curves of given genus
 Publ. Math. IHES
, 1969
"... Fix an algebraically closed field k. Let Mg be the moduli space of curves of genus g over k. The main result of this note is that Mg is irreducible for every k. Of course, whether or not M s is irreducible depends only on the characteristic of k. When the characteristic s o, we can assume that k ~ ..."
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Cited by 512 (2 self)
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Fix an algebraically closed field k. Let Mg be the moduli space of curves of genus g over k. The main result of this note is that Mg is irreducible for every k. Of course, whether or not M s is irreducible depends only on the characteristic of k. When the characteristic s o, we can assume that k
Stacked generalization
 Neural Networks
, 1992
"... Abstract: This paper introduces stacked generalization, a scheme for minimizing the generalization error rate of one or more generalizers. Stacked generalization works by deducing the biases of the generalizer(s) with respect to a provided learning set. This deduction proceeds by generalizing in a s ..."
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Cited by 714 (8 self)
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second space whose inputs are (for example) the guesses of the original generalizers when taught with part of the learning set and trying to guess the rest of it, and whose output is (for example) the correct guess. When used with multiple generalizers, stacked generalization can be seen as a more
Actions as spacetime shapes
 In ICCV
, 2005
"... Human action in video sequences can be seen as silhouettes of a moving torso and protruding limbs undergoing articulated motion. We regard human actions as threedimensional shapes induced by the silhouettes in the spacetime volume. We adopt a recent approach [14] for analyzing 2D shapes and genera ..."
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Cited by 642 (4 self)
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and generalize it to deal with volumetric spacetime action shapes. Our method utilizes properties of the solution to the Poisson equation to extract spacetime features such as local spacetime saliency, action dynamics, shape structure and orientation. We show that these features are useful for action
Spacetime Interest Points
 IN ICCV
, 2003
"... Local image features or interest points provide compact and abstract representations of patterns in an image. In this paper, we propose to extend the notion of spatial interest points into the spatiotemporal domain and show how the resulting features often reflect interesting events that can be use ..."
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Cited by 791 (22 self)
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Local image features or interest points provide compact and abstract representations of patterns in an image. In this paper, we propose to extend the notion of spatial interest points into the spatiotemporal domain and show how the resulting features often reflect interesting events that can be used for a compact representation of video data as well as for its interpretation.. To detect
ScaleSpace Theory in Computer Vision
, 1994
"... A basic problem when deriving information from measured data, such as images, originates from the fact that objects in the world, and hence image structures, exist as meaningful entities only over certain ranges of scale. "ScaleSpace Theory in Computer Vision" describes a formal theory fo ..."
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Cited by 617 (21 self)
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A basic problem when deriving information from measured data, such as images, originates from the fact that objects in the world, and hence image structures, exist as meaningful entities only over certain ranges of scale. "ScaleSpace Theory in Computer Vision" describes a formal theory
Results 1  10
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2,894,203