@InProceedings{CostaJooKöbe:1993:DiNeNe,
author = "Costa, Luciano da Fontoura and Joo, Javier Montenegro and
K{\"o}berle, Roland",
affiliation = "{Instituto de F{\'{\i}}sica e Qu{\'{\i}}mica de S{\~a}o
Carlos (IFQSC) da Universidade de S{\~a}o Paulo (USP)} and
{Instituto de F{\'{\i}}sica e Qu{\'{\i}}mica de S{\~a}o
Carlos (IFQSC) da Universidade de S{\~a}o Paulo (USP)} and
{Instituto de F{\'{\i}}sica e Qu{\'{\i}}mica de S{\~a}o
Carlos (IFQSC) da Universidade de S{\~a}o Paulo (USP)}",
title = "Distance-discriminator neural networks for classification and
pattern recognition",
booktitle = "Anais...",
year = "1993",
editor = "Figueiredo, Luiz Henrique de and Gomes, Jonas de Miranda",
pages = "221--229",
organization = "Simp{\'o}sio Brasileiro de Computa{\c{c}}{\~a}o Gr{\'a}fica e
Processamento de Imagens, 6. (SIBGRAPI)",
publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
address = "Porto Alegre",
keywords = "discriminator neural, Distance-discriminator neurons,
Distance-discriminator Neural Networks, interfaces.",
abstract = "Distance-discriminator neurons DDNs and their combination in
Distance-discriminator Neural Networks DDNNs are proposed and
discussed. DDNs, based on distance metric concepts, are able to
discriminate whether a given point (x,y) belongs to a closed
region such as diamond-, rectangle and ellipse-bound regions,
which are tasks traditionally performed by perceptrons. DDNs can
also be straightforwardly modified in order to discriminate hollow
regions having as outer boundaries the above mentioned geometrical
figures or even combinations of them. The principal advantage of
DDNNs over perceptrons is a substantial reduction of execution
time and/or the amount of required hardware operators: many
polygonal classification regions which would otherwise demand
large perceptron structures can be discriminated with only a few
DDNNs. DDNNs can also be easily programmed by design or
automatically with the help of the hough transform. Such issues as
well as the relative advantages of DDNNs and perceptrons and a
complete application example are presented and discussed in the
present paper.",
conference-location = "Recife, PE, Brazil",
conference-year = "19-22 Oct. 1993",
isbn = "978-85-7669-271-3",
language = "en",
ibi = "8JMKD3MGPBW34M/3D85H2S",
url = "http://urlib.net/ibi/8JMKD3MGPBW34M/3D85H2S",
targetfile = "26 Distance discriminator neural networks.pdf",
type = "Vis{\~a}o por Computador",
volume = "1",
urlaccessdate = "2024, Apr. 29"
}