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    • Revista IJIMAI
    • 2014
    • vol. 3, nº 1, december 2014
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    • UNIR REVISTAS
    • Revista IJIMAI
    • 2014
    • vol. 3, nº 1, december 2014
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    Neural Networks through Shared Maps in Mobile Devices

    Autor: 
    Raveane, William
    ;
    González Arrieta, María Angélica
    Fecha: 
    12/2014
    Palabra clave: 
    computer vision; graphical model; image recognition; mobile device; neural network; IJIMAI
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/9818
    DOI: 
    http://dx.doi.org/10.9781/ijimai.2014.314
    Dirección web: 
    https://www.ijimai.org/journal/node/706
    Open Access
    Resumen:
    We introduce a hybrid system composed of a convolutional neural network and a discrete graphical model for image recognition. This system improves upon traditional sliding window techniques for analysis of an image larger than the training data by effectively processing the full input scene through the neural network in less time. The final result is then inferred from the neural network output through energy minimization to reach a more precize localization than what traditional maximum value class comparisons yield. These results are apt for applying this process in a mobile device for real time image recognition.
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