PADO: A New Learning Architecture for Object Recognition

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

@InCollection{teller:1995:PADO,
  author =       "Astro Teller and Manuela Veloso",
  title =        "PADO: A New Learning Architecture for Object
                 Recognition",
  booktitle =    "Symbolic Visual Learning",
  publisher =    "Oxford University Press",
  year =         "1996",
  editor =       "Katsushi Ikeuchi and Manuela Veloso",
  pages =        "81--116",
  keywords =     "genetic algorithms, genetic programming, memory",
  URL =          "http://www.cs.cmu.edu/afs/cs/usr/astro/public/papers/PADO.ps",
  abstract =     "Most artificial intelligence systems today work on
                 simple problems and artificial domains because they
                 rely on the accurate sensing of the task world. Object
                 recognition is a crucial part of the sensing challenge
                 and machine learning stands in a position to catapult
                 object recognition into real world domains. Given that,
                 to date, machine learning has not delivered general
                 object recognition, we propose a different point of
                 attack: the learning architectures themselves. We have
                 developed a method for directly learning and combining
                 algorithms in a new way that imposes little burden on
                 or bias from the humans involved. This learning
                 architecture, PADO, and the new results it brings to
                 the problem of natural image object recognition is the
                 focus of this chapter.",
  notes =        "This is NOT the same as \cite{TechTeller}. The overlap
                 is about 20 of the 34 pages but it is different
                 enough",
  size =         "34 pages",
}

Genetic Programming entries for Astro Teller Manuela Veloso

Citations