On-Line Digit Recognition using Off-Line Features

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

@InProceedings{oai:CiteSeerPSU:553870,
  title =        "On-Line Digit Recognition using Off-Line Features",
  author =       "A. Teredesai and E. Ratzlaff and J. Subrahmonia and 
                 V. Govindaraju",
  year =         "2002",
  booktitle =    "Indian Conference on Computer Vision, Graphics and
                 Image Processing (ICVGIP'02)",
  address =      "SAC, Ahmedabad, India",
  keywords =     "genetic algorithms, genetic programming",
  citeseer-isreferencedby = "oai:CiteSeerPSU:92773;
                 oai:CiteSeerPSU:281360; oai:CiteSeerPSU:428408",
  citeseer-references = "oai:CiteSeerPSU:125873",
  annote =       "The Pennsylvania State University CiteSeer Archives",
  language =     "en",
  oai =          "oai:CiteSeerPSU:553870",
  rights =       "unrestricted",
  URL =          "http://www.ee.iitb.ac.in/~icvgip/PAPERS/321.pdf",
  URL =          "http://citeseer.ist.psu.edu/553870.html",
  size =         "6 pages",
  abstract =     "This paper describes a classification method for
                 on-line handwritten digits based on off-line image
                 representations. The goal is to use image-based
                 features to improve classifier accuracy for on-line
                 handwritten input. In this paper we describe an initial
                 framework that can be used to achieve this goal. This
                 framework for handwritten digit classification is based
                 on genetic programming (GP). Several issues in
                 preprocessing, transformation of data from on-line to
                 off-line domains and feature extraction are described.
                 Results are reported on the UNIPEN digit dataset.",
  notes =        "http://www.ee.iitb.ac.in/~icvgip/schedule.htm",
}

Genetic Programming entries for Ankur M Teredesai E Ratzlaff J Subrahmonia Venugopal Govindaraju

Citations