Hybrid Evolvable Hardware for automatic generation of image filters

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@Article{Almeida:2018:ICAE,
  author =       "M. A. Almeida and E. C. Pedrino",
  title =        "Hybrid Evolvable Hardware for automatic generation of
                 image filters",
  journal =      "Integrated Computer-Aided Engineering",
  year =         "2018",
  volume =       "25",
  number =       "3",
  pages =        "289--303",
  keywords =     "genetic algorithms, genetic programming, Evolvable
                 Hardware, FPGA, virtual reconfigurable architecture",
  ISSN =         "1069-2509",
  DOI =          "doi:10.3233/ICA-180561",
  size =         "15 pages",
  abstract =     "In this article, a new framework is proposed and
                 implemented for automatic generation of image filters
                 in reconfigurable hardware (FPGA), called H-EHW
                 (Hybrid-Evolvable Hardware). This consists basically of
                 two modules. The first (training module) is responsible
                 for the automatic generation of solutions (filters).
                 The second (fusion module) converts such solutions into
                 hardware, thus creating a virtual and reconfigurable
                 architecture for fast image processing. Monochromatic
                 pairs of images are used for the system training and
                 testing. Extensive tests show that there are several
                 benefits of the proposed system when compared to other
                 similar systems described in the literature, such as:
                 reduced phenotype length (generated circuit), reduced
                 reconfiguration time, greater hardware reconfiguration
                 flexibility and no more need for the manipulation of
                 the bitstream of the FPGA for circuit evolution (a
                 problem often encountered in practice by designers).",
}

Genetic Programming entries for M A Almeida Emerson Carlos Pedrino

Citations