The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform

T. Birkholzer - One of the best experts on this subject based on the ideXlab platform.

  • Reinforcement of Linear Structure using parametrized relaxation labeling
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992
    Co-Authors: James S. Duncan, T. Birkholzer
    Abstract:

    The problem of reinforcing local evidence of Linear Structure while suppressing unwanted information in noisy images is considered, using a modified form of relaxation labeling. The methodology is based on parametrizing a continuous set of orientation labels via a single vector and using a sigmoidal thresholding function to bias neighborhood influence and ensure convergence to a meaningful stable state. Label strength and label/no-label decisions are incorporated into a single functional. Optimal points of the functional represent the cases where as many pixels (objects) as possible have achieved the desirable Linear-Structure-reinforced and noise-suppressed labelings. Three different Linear Structure reinforcement tasks are considered within the general framework: edge reinforcement, edge reinforcement with thinning, and bar (line segment) reinforcement. Results from several image data sets are presented. This approach can directly handle continuous feature information from low-level image analysis operators, and the computational complexity of labeling is reduced. >

Birkhölzerthomas - One of the best experts on this subject based on the ideXlab platform.

James S. Duncan - One of the best experts on this subject based on the ideXlab platform.

  • Reinforcement of Linear Structure using parametrized relaxation labeling
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992
    Co-Authors: James S. Duncan, T. Birkholzer
    Abstract:

    The problem of reinforcing local evidence of Linear Structure while suppressing unwanted information in noisy images is considered, using a modified form of relaxation labeling. The methodology is based on parametrizing a continuous set of orientation labels via a single vector and using a sigmoidal thresholding function to bias neighborhood influence and ensure convergence to a meaningful stable state. Label strength and label/no-label decisions are incorporated into a single functional. Optimal points of the functional represent the cases where as many pixels (objects) as possible have achieved the desirable Linear-Structure-reinforced and noise-suppressed labelings. Three different Linear Structure reinforcement tasks are considered within the general framework: edge reinforcement, edge reinforcement with thinning, and bar (line segment) reinforcement. Results from several image data sets are presented. This approach can directly handle continuous feature information from low-level image analysis operators, and the computational complexity of labeling is reduced. >

Nicholas P. Warner - One of the best experts on this subject based on the ideXlab platform.

  • supersymmetric solutions in six dimensions a Linear Structure
    Journal of High Energy Physics, 2012
    Co-Authors: Iosif Bena, Stefano Giusto, Masaki Shigemori, Nicholas P. Warner
    Abstract:

    The equations underlying all supersymmetric solutions of six-dimensional min- imal ungauged supergravity coupled to an anti-self-dual tensor multiplet have been known for quite a while, and their complicated non-Linear form has hindered all attempts to sys- tematically understand and construct supersymmetric solutions. In this paper we show that, by suitably re-parameterizing these equations, one can find a Structure that allows one to construct supersymmetric solutions by solving a sequence of Linear equations. We then illustrate this method by constructing a new class of geometries describing several parallel spirals carrying D1, D5 and P charge and parameterized by four arbitrary func- tions of one variable. A similar Linear Structure is known to exist in five dimensions, where it underlies the black hole, black ring and corresponding microstate geometries. The un- expected generalization of this to six dimensions will have important applications to the construction of new, more general such geometries.

  • Supersymmetric Solutions in Six Dimensions: A Linear Structure
    Journal of High Energy Physics, 2012
    Co-Authors: Iosif Bena, Stefano Giusto, Masaki Shigemori, Nicholas P. Warner
    Abstract:

    The equations underlying all supersymmetric solutions of six-dimensional minimal ungauged supergravity coupled to an anti-self-dual tensor multiplet have been known for quite a while, and their complicated non-Linear form has hindered all attempts to systematically understand and construct BPS solutions. In this paper we show that, by suitably re-parameterizing these equations, one can find a Structure that allows one to construct supersymmetric solutions by solving a sequence of Linear equations. We then illustrate this method by constructing a new class of geometries describing several parallel spirals carrying D1, D5 and P charge and parameterized by four arbitrary functions of one variable. A similar Linear Structure is known to exist in five dimensions, where it underlies the black hole, black ring and corresponding microstate geometries. The unexpected generalization of this to six dimensions will have important applications to the construction of new, more general such geometries.

S Duncanjames - One of the best experts on this subject based on the ideXlab platform.