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Neural Networks through Shared Maps in Mobile Devices

William Raveane, Maria Angelica Gonzalez Arrieta
Universidad de Salmanca, Spain
International Journal of Interactive Multimedia and Artificial Intelligence, Vol. 3, Number 1, 28-35, 2014

@article{raveane2014neural,

   title={Neural Networks through Shared Maps in Mobile Devices},

   author={Raveane, William and Arrieta, Mar{‘i}a Ang{‘e}lica Gonz{‘a}lez},

   year={2014}

}

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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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