Application of Genetic Programming and Genetic Algorithm in Evolving Emotion Recognition Module

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@InProceedings{Yusuf:2015:CEC,
  author =       "Rahadian Yusuf and Ivan Tanev and 
                 Katsunori Shimohara",
  title =        "Application of Genetic Programming and Genetic
                 Algorithm in Evolving Emotion Recognition Module",
  booktitle =    "Proceedings of 2015 IEEE Congress on Evolutionary
                 Computation (CEC 2015)",
  year =         "2015",
  editor =       "Yadahiko Murata",
  pages =        "1444--1449",
  address =      "Sendai, Japan",
  month =        "25-28 " # may,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CEC.2015.7257058",
  abstract =     "This paper will discuss about implementation of a
                 voting system and weighted credibility to augment
                 evolution process of an emotion recognition module. The
                 evolution process of the emotion recognition module is
                 one part of ongoing research on designing an
                 intelligent agent capable of emotion recognition,
                 interaction, and expression. Genetic programming
                 evolves the classifiers, while genetic algorithm
                 evolves the weighted credibility as a modification of
                 parallel voting systems. The experimental results
                 suggest that the implementation of weighted credibility
                 evolution improves the performance of training, in the
                 form of significantly reduced training time needed.",
  notes =        "1710 hrs 15440 CEC2015",
}

Genetic Programming entries for Rahadian Yusuf Ivan T Tanev Katsunori Shimohara

Citations