Imagery pattern recognition (IPR) is becoming more challenging as image resolutions continue to improve and algorithms become more complex. Systems for analysis are being developed on increasingly diverse and heterogeneous platforms, from hardware support using field programmable gate arrays, graphics processing units, and Cell processors to high performance computers, featuring multi-core processors and shared memory communications. Given the complexity of modern IPR systems, neither analytical nor adaptive methods are sufficient to understand the shortfalls of an approach to IPR for any particular architecture. Our test harness implements an adaptive, experimental approach that can be used to quickly estimate performance and perform validation. A case study is implemented that implements the test harness for a publish/subscribe architecture, and in which several approaches for brokering are compared in a pub/sub implementation.


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    Title :

    Imagery Pattern Recognition and Pub/Sub Information Management


    Contributors:


    Publication date :

    2007-10-01


    Size :

    354080 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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