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Octavio Israel Rentería Vidales

   »  Generación: Septiembre2017
   »  Grado: Maestría en Computación
   »  Asesor: Juan Carlos Cuevas Tello
   »  Co-asesor: Dr. Mariano José Juan Rivera Meraz
   »  Línea de Investigación: Ninguna
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Compression of Convolutional Neural Networks on an embedded system applied to optical flow


The goal of this work is taking a well-known model for Optical Flow (like FlowNet 2.0) and compress it so that it can be executed on a low power devices like the Intel Movidius chip, while preserving accuracy. It is proposed to investigate and apply some techniques reported in the literature for compression of Convolutional Neural Networks and measure performance and accuracy in low-consumption hardware.