PADO: A New Learning Architecture for Object Recognition

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@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