Random projection (RP) is a common technique for dimensionality reduction under L-2 norm for which many significant space embedding results have been demonstrated. In particular, random projection techniques can yield...
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(纸本)9783540921905
Random projection (RP) is a common technique for dimensionality reduction under L-2 norm for which many significant space embedding results have been demonstrated. In particular, random projection techniques can yield sharp results for R-d under the L-2 norm in time linear to the product of the number of data points and dimensionalities in question. Inspired by the use of symmetric probability distributions in previous work, we propose a RP algorithm based on the hyper-spherical symmetry and give its probabilistic analyses based on Beta and Gaussian distribution.
The automated detection of process-induced defects such as tooling marks is a common and important problem in machine vision. Such defects are often distinguishable from natural flaws and other features by their geome...
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The automated detection of process-induced defects such as tooling marks is a common and important problem in machine vision. Such defects are often distinguishable from natural flaws and other features by their geometric form, for example their circularity or linearity. This paper discusses the automated inspection of polished stone, where process-induced defects present as circular arcs. This is a particularly demanding circle detection problem due to the large radii and disrupted form of the arcs, the complex nature of the stone surface, the presence of other natural flaws and the fact that each circle is represented by a relatively small proportion of its total boundary. Once detected and characterized, data relating to the defects may be used to adaptively control the polishing process. We discuss the hardware requirements of imaging such a surface and present a novel implementation of a random;ed circle detection algorithm that is able to reliably detect these defects. The algorithm minimizes the number of iterations required, based on a failure probability specified by the user, thus providing optimum efficiency for a specified confidence whilst requiring no prior knowledge of the image. The probabilities of spurious results are also analyzed, and an optimization routine introduced to address the inaccuracies often associated with randomized techniques. Experimental results demonstrate the validity of this approach. (c) 2005 Published by Elsevier B.V.
This paper presents a randomized parallel algorithm for computing planar Voronoi diagrams of n point sites according to symmetric convex distance functions. This algorithm uses, with high probability, O(n log(n)/p) lo...
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This paper presents a randomized parallel algorithm for computing planar Voronoi diagrams of n point sites according to symmetric convex distance functions. This algorithm uses, with high probability, O(n log(n)/p) local computation time and O(n/p) space on the processors plus time for O(1) communication rounds on a coarse grained multicomputer with p processors. (C) 2001 Elsevier Science B.V. All rights reserved.
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