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An Expandable Hardware Platform for Implementation of CNN-Based Applications

  • J. Javier Martínez-Álvarez
  • F. Javier Garrigós-Guerrero
  • F. Javier Toledo-Moreo
  • J. Manuel Ferrández-Vicente
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6687)

Abstract

This paper proposes a standalone system for real-time processing of video streams using CNNs. The computing platform is easily expandable and customizable for any application. This is achieved by using a modular approach both for the CNN architecture itself and for its hardware implementation. Several FPGA-based processing modules can be cascaded together with a video acquisition stage and an output interface to a framegrabber for video output storage, all sharing a common communication interface. The pre-verified CNN components, the modular architecture, and the expandable hardware platform provide an excellent workbench for fast and confident developing of CNN applications.

Keywords

Video Stream Output Port Input Port Cellular Neural Network Register Bank 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • J. Javier Martínez-Álvarez
    • 1
  • F. Javier Garrigós-Guerrero
    • 1
  • F. Javier Toledo-Moreo
    • 1
  • J. Manuel Ferrández-Vicente
    • 1
  1. 1.Dpto. Electrónica, Tecnología de Computadoras y ProyectosUniversidad Politécnica de CartagenaCartagenaSpain

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