@InProceedings{PereiraPapAlmTorAmo:2013:MuLaOp,
author = "Pereira, Luis Augusto Martins and Papa, Joao Paulo and Almeida,
Jurandy and Torres, Ricardo da Silva and Amorim, Willian
Paraguassu",
affiliation = "{UNESP - Univ Estadual Paulista} and {UNESP - Univ Estadual
Paulista} and {University of Campinas} and {University of
Campinas} and {Federal University of Mato Grosso do Sul}",
title = "A Multiple Labeling-based Optimum-Path Forest for Video Content
Classification",
booktitle = "Proceedings...",
year = "2013",
editor = "Boyer, Kim and Hirata, Nina and Nedel, Luciana and Silva,
Claudio",
organization = "Conference on Graphics, Patterns and Images, 26. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "Image motion analysis, Video signal classification, multi-label
learning, Optimum-Path Forest.",
abstract = "Multiple-labeling classification approaches attempt to handle
applications that associate more than one label to a given sample.
Since we have an increasing number of systems that are guided by
such assumption, in this paper we have presented a
multiple-labeling approach for the Optimum-Path Forest (OPF)
classifier based on the problem transformation method. In order to
validate our proposal, a multi-labeled video classification
dataset has been used to compare OPF against three other
classifiers and another variant of the OPF classifier based on a
k-neighborhood. The results have shown the validity of the
OPF-based classifiers for multi-labeling classification
problems.",
conference-location = "Arequipa, Peru",
conference-year = "5-8 Aug. 2013",
doi = "10.1109/SIBGRAPI.2013.53",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2013.53",
language = "en",
ibi = "8JMKD3MGPBW34M/3EDJGRP",
url = "http://urlib.net/ibi/8JMKD3MGPBW34M/3EDJGRP",
targetfile = "camera_ready.pdf",
urlaccessdate = "2024, May 02"
}