@InProceedings{AndradePeixAraú:1994:SeImRe,
author = "Andrade, Marcos Carneiro de and Peixoto, Fabiano Cruz and
Ara{\'u}jo, Arnaldo de Albuquerque",
affiliation = "{Departamento de Ci{\^e}ncia da Computa{\c{c}}{\~a}o (DCC) da
Universidade Federal de Minas Gerais (UFMG)} and {Departamento de
Ci{\^e}ncia da Computa{\c{c}}{\~a}o (DCC) da Universidade
Federal de Minas Gerais (UFMG)} and {Departamento de Ci{\^e}ncia
da Computa{\c{c}}{\~a}o (DCC) da Universidade Federal de Minas
Gerais (UFMG)}",
title = "Segmenta{\c{c}}{\~a}o de imagens atrav{\'e}s de rede neuronal
por satisfa{\c{c}}{\~a}o de restri{\c{c}}{\~o}es em ambiente
paralelo",
booktitle = "Anais...",
year = "1994",
editor = "Freitas, Carla dal Sasso and Geus, Klaus de and Scheer,
S{\'e}rgio",
pages = "47--52",
organization = "Simp{\'o}sio Brasileiro de Computa{\c{c}}{\~a}o Gr{\'a}fica e
Processamento de Imagens, 7. (SIBGRAPI)",
publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
address = "Porto Alegre",
keywords = "segmenta{\c{c}}{\~a}o de imagens, rede neuronal, ambiente
paralelo, processamento de imagens.",
abstract = "The constraint satisfaction neural network CSNN, proposed by Chen
is here implemented in a massively parallel SIMD machine. The CSNN
can be viewed as a set of interconnected neurons, whose topology
and connections are used to represent constraints in a Constraint
Satisfaction Problem CSP. The neural network ierates until it
converges to a consistent state. In this state all constraints are
satisfied and the solution outlines the segmented areas. This
region segmentation technique has been applied to images and is
very promising.",
conference-location = "Curitiba, PR, Brazil",
conference-year = "9-11 Nov. 1994",
isbn = "978-85-7669-272-0",
language = "pt",
ibi = "8JMKD3MGPBW34M/3DDB8A8",
url = "http://urlib.net/ibi/8JMKD3MGPBW34M/3DDB8A8",
targetfile = "7 Segmentacao de imagens atraves de rede neuronal.pdf",
type = "Modelos e T{\'e}cnicas para Processamento de Imagens",
volume = "1",
urlaccessdate = "2024, Apr. 28"
}