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Now showing items 1 - 16 of 3579

  • Statistical Image Processing and Graphics.by Edward J. Wegman; Douglas J. DePriest

    Review by: Brian S. Yandell  

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  • Statistical Image Processing and Graphicsby Edward J. Wegman; Douglas J. DePriest

    Review by: Ronald Thisted  

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  • Software analysis system and method of use

    Systems and Methods are utilized for determining a software signature. A software program in a form of a sequence of instructions of the software program is obained. The software program is clustered into a software family. A signature for each software family is generated.
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  • Statistical Image Processing and Graphics.by Edward J. Wegman; Douglas J. DePriest

    Review by: J. C. Gower  

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  • Special issue of statistical analysis and data mining

    Edward J. Wegman  

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  • Special issue of statistical analysis and data mining

    Edward J. Wegman  

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  • Natural homogeneous coordinates

    Edward J. Wegman   Yasmin H. Said  

    Abstract The natural homogeneous coordinate system is the analog of the Cartesian coordinate system for projective geometry. Roughly speaking a projective geometry adds an axiom that parallel lines meet at a point at infinity. This removes the impediment to line-point duality that is found in traditional Euclidean geometry. The natural homogeneous coordinate system is surprisingly useful in a number of applications including computer graphics and statistical data visualization. In this article, we describe the axioms of projective geometry, introduce the formalism of natural homogeneous coordinates, and illustrate their use with four applications. WIREs Comp Stat 2010 2 678–685 DOI: 10.1002/wics.122 For further resources related to this article, please visit the WIREs website.
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  • Machine learning, data mining, and computational statistics applications

    Edward J. Wegman   Yasmin H. Said   David W. Scott  

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  • Policy analysis and action decision tool

    Using stochastic directed graphs, a social network stochastic directed graph model allows for policy analysis and action. An activity generator may be used for creating agents that represent a population stratum. Agents may be proportionally selected to the size of the population stratum and representative activities that are associated with said population stratum. Agents have one or more conditional probabilities attached to the activities, which indicate the likelihood of interaction between agents and one or more agents or actors. Outcomes for the interactions may be accumulated. Based on these outcomes, which include benign and acute, a multinomial probability distribution may be estimated.
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  • WIREs is a WINNER

    Edward J. Wegman   Yasmin H. Said   David W. Scott  

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  • Introducing WIREs Computational Statistics

    Edward J. Wegman   Yasmin H. Said   David W. Scott  

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  • WIREs between Washington, DC and Durban, South Africa

    Edward J. Wegman   Yasmin H. Said   David W. Scott  

    Abstract For further resources related to this article, please visit the WIREs website.
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  • Statistical Signal Processing.by Edward J. Wegman; James G. Smith

    Review by: W. D. Ray  

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  • Adaptive Multi-Modal Data Mining and Fusion For Autonomous Intelligence Discovery

    Edward J. Wegman  

    This proposal addressed the autonomous discovery of relevant information in massive, complex, dynamic text and imagery streams. We began development of a prototype system to mine, filter and fuse multi-modal data streams and dynamically interact with the analysts to improve their efficiency through feedbacks and autonomous adaptation of the algorithms. The plan was to implement four core capabilities: 1) Text and image mining for feature extraction, 2) Multi-modal data fusion, 3) Agent-based adaptive information filtering, 4) Cognitively friendly information visualization. The focus in the first phase of the work was multilingual text search systems as well as geospatial mapping of documents and images.
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  • Visual data mining

    Edward J. Wegman  

    Data mining strategies are usually applied to opportunistically collected data and frequently focus on the discovery of structure such as clusters, bumps, trends, periodicities, associations and correlations, quantization and granularity, and other structures for which a visual data analysis is very appropriate and quite likely to yield insight. However, data mining strategies are often applied to massive data sets where visualization may not be very successful because of the limits of both screen resolution, human visual system resolution as well as the limits of available computational resources. In this paper I suggest some strategies for overcoming such limitations and illustrate visual data mining with some examples of successful attacks on high-dimensional and large data sets.
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  • Final Report on Massive Data Sets: Visualization and Analysis

    Edward J. Wegman  

    This project argued that the downsizing of U.S. Army implies a profound change in the way the Army carries out its war-fighting mission. There will be an increased reliance on technology. Because these are technology based warfare areas, there will be massive data sets generated electronically as part of the normal operations. The ability to analyze such data sets is crucial to the prosecution of a military engagement in 2000 and beyond since it is in the structure of these data sets that crucial information about the timing, size and nature of enemy attacks is likely to be found. We have developed several methods for carrying out the analysis of massive data sets, in particular we have carried out research to reduce the computational complexity of clustering algorithms, to reduce the complexity of visualization methods and to increase the ability of visualization methods to handle massive data sets, and research on quantization methods for massive data sets.
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