Genetic Programming for Generative Learning and Recognition of Hand-Drawn Shapes

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InCollection{Jaskowski:2009:EIASP,
  author =       "Wojciech Jaskowski and Krzysztof Krawiec and 
                 Bartosz Wieloch",
  title =        "Genetic Programming for Generative Learning and
                 Recognition of Hand-Drawn Shapes",
  booktitle =    "Evolutionary Image Analysis and Signal Processing",
  publisher =    "Springer",
  year =         "2009",
  editor =       "Stefano Cagnoni",
  volume =       "213",
  series =       "Studies in Computational Intelligence",
  pages =        "73--90",
  address =      "Berlin / Heidelberg",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-01635-6",
  ISSN =         "1860-949X",
  DOI =          "doi:10.1007/978-3-642-01636-3_5",
  abstract =     "We propose a novel method of evolutionary visual
                 learning that uses a generative approach to assess the
                 learner's ability to recognise image contents. Each
                 learner, implemented as a genetic programming (GP)
                 individual, processes visual primitives that represent
                 local salient features derived from the input image.
                 The learner analyses the visual primitives, which
                 involves mostly their grouping and selection,
                 eventually producing a hierarchy of visual primitives
                 build upon the input image. Based on that it provides
                 partial reproduction of the shapes of the analysed
                 objects and is evaluated according to the quality of
                 that reproduction.We present the method in detail and
                 verify it experimentally on the real-world task of
                 recognition of hand-drawn shapes. In particular, we
                 show how GP individuals trained on examples from
                 different decision classes can be combined to build a
                 complete multiclass recognition system. We compare such
                 recognition systems to reference methods, showing that
                 our generative learning approach provides similar
                 results. This chapter also contains detailed analysis
                 of processing carried out by an exemplary individual.",
  notes =        "Institute of Computing Science, Poznan University of
                 Technology,Poland EvoISAP, EvoNET, EvoStar",
}

Genetic Programming entries for Wojciech Jaskowski Krzysztof Krawiec Bartosz Wieloch

Citations