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Hierarchical model for pattern recognition based on parallel and distributed computing

Hierarchical model for pattern recognition based on parallel and distributed computing. Olivier Bornet , University Joseph Fourier Grenoble Martin Kalany , Vienna University of Technology Scientific advisor: Sergey V. Axyonov. Motivation and targets. Motivation

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Hierarchical model for pattern recognition based on parallel and distributed computing

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  1. Hierarchical model for pattern recognition based on parallel and distributed computing Olivier Bornet, University Joseph Fourier Grenoble Martin Kalany, Vienna University of Technology Scientific advisor: Sergey V. Axyonov

  2. Motivation and targets • Motivation • Objectrecognitionis a widelyusedfeaturefromindustrialrobotstoautonomousvehicles • Multiple-Core processorsarenowfairlycommon • Image proccessingishighlydepending on processor-intensive operationswithmatrices • Targets • Create andimplement a model thatiscapableofrecognizing simple features • Useconcurrentanddistributedprogrammingtechniquestomassivlydecreaseexecution time Olivier Bornet, Martin Kalany: Hierarchical model for pattern recognition based on parallel and distributed computing

  3. Overview of the model Olivier Bornet, Martin Kalany: Hierarchical model for pattern recognition based on parallel and distributed computing

  4. Mathematical model • Filter layer • Detects rather small features like lines with different angles and features • Uses different Gabor filters for features detection • -Feature angle • -Feature width • -Pixel locationinsideofcellreceptivefield - Output of filter cell with location • - Receptive field • - Gray-scaleinput Olivier Bornet, Martin Kalany: Hierarchical model for pattern recognition based on parallel and distributed computing

  5. Mathematical model • MAX layer • Combination of the results of several different Gabor filters • Detect local features regardless of it‘s width - Output of MAX cell with location - Plane index • Kohonen layer • Stores information about more • complex features • - Estimates Euclidian distance between • MAX layer outcomes and stored features Olivier Bornet, Martin Kalany: Hierarchical model for pattern recognition based on parallel and distributed computing

  6. Mathematical model • View-tuned units (VTU) • - Remembers all complex features of • entire object • Uses radial-basis functions to estimate • similarity measure between input object • and stored patterns VTU output: - Kohonen layer outputs Olivier Bornet, Martin Kalany: Hierarchical model for pattern recognition based on parallel and distributed computing

  7. Algorithm Olivier Bornet, Martin Kalany: Hierarchical model for pattern recognition based on parallel and distributed computing

  8. OpenMP &MPI Olivier Bornet, Martin Kalany: Hierarchical model for pattern recognition based on parallel and distributed computing

  9. Results Constructed model All layers successfully implemented Studied principles and usage of parallel and distributed programming Parallel programming already in use for Kohonen layer Olivier Bornet, Martin Kalany: Hierarchical model for pattern recognition based on parallel and distributed computing

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