@InProceedings{TorrećoRoe:1994:MiOpAp,
author = "Torre{\~a}o, Jos{\'e} Ricardo A. and Roe, Edward",
affiliation = "{Departamento de Inform{\'a}tica da Universidade Federal de
Pernambuco (UFPE)} and {Departamento de Inform{\'a}tica da
Universidade Federal de Pernambuco (UFPE)}",
title = "Microcanonical optimization applied to visual processing: an
assessment",
booktitle = "Anais...",
year = "1994",
editor = "Freitas, Carla dal Sasso and Geus, Klaus de and Scheer,
S{\'e}rgio",
pages = "221--228",
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 = "visual processing, microcanonical optimization algorithm,
Barnards microcanonical.",
abstract = "The microcanonical optimization algorithm (µO) is an algorithm
based on the microcanonical simulation techniques of statistical
physics, which has been recently proposed as a suitable
alternative to the simulated annealing approaches. The µO
algorithm retains all of the positive features of the
microcanonical annealing introduced by Barnard (which follows the
pioneering work by Creutz), but avoids the necessity of an
annealing schedule, thus resulting in improved computational
efficiency. Here we present applications of the µO algorithm to
some prototypical visual and show that it performs better than the
traditional, or canonical, simulated annealing (SA) and then
Barnards microcanonical annealing (MA).",
conference-location = "Curitiba, PR, Brazil",
conference-year = "9-11 Nov. 1994",
isbn = "978-85-7669-272-0",
language = "en",
ibi = "8JMKD3MGPBW34M/3DEAGL8",
url = "http://urlib.net/ibi/8JMKD3MGPBW34M/3DEAGL8",
targetfile = "29 Microcanonial optimization applied to visual.pdf",
type = "M{\'e}todos e T{\'e}cnicas em Processamento Visual",
volume = "1",
urlaccessdate = "2024, Apr. 29"
}