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GPGPU Volume Classification using SimpleOpenCL

Oscar Amoros, Sergio Escalera, Anna Puig, Maria Salamo
Dept. Matematica Aplicada i Analisi, Universitat de Barcelona, Spain
VI CVC Workshop on the progress of Research & Development (CVCR&D2011), pp. 136-141, 2011

@article{amoros2011gpgpu,

   title={GPGPU Volume Classification using SimpleOpenCL},

   author={Amoros, O. and Escalera, S. and Puig, A. and Salam{‘o}, M.},

   year={2011}

}

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In volume visualization, the definition of the regions of interest is inherently an iterative trialand-error process finding out the best parameters to classify and render the final image. In this work, we present a general framework for training multi-class classifiers using Error-Correcting Output Codes. Moreover, we propose a GPGPU parallelization system using SimpleOpenCL, an OpenSource library we created to make easier the use of OpenCL. Results show accurate classification results as well as good speed ups.
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