@InProceedings{ParreiraDutPanRuwLu:2015:MéCoCl,
author = "Parreira, Michelle de Oliveira and Dutra, Luciano Vieira and
Pantale{\~a}o, Eliana and Ruwer, Sherfis Gibran and Lu,
Dengsheng",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {} and {Instituto
Nacional de Pesquisas Espaciais (INPE)}",
title = "Sistema Classificador Parreira: um m{\'e}todo de
combina{\c{c}}{\~a}o de classifica{\c{c}}{\~o}es por pares de
classes",
booktitle = "Anais...",
year = "2015",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "2929--2936",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "Traditional procedures for classifying remote sensing images use
the concept of competitive classification. It chooses the
classification that achieves the best results among the tested
metrics. The problem within this procedure is the loss of
information for some class when just one classifier is chosen,
since each classifier generates different sampling error. This
paper presents the first part of the develop-ment of a new
Classification System, called Parreira. It combines the results of
classifiers to analyze the discriminability of class pairs. From
an image, a set of classes and their training ROIs, the system
gener-ates all possible combinations of classes in pairs. By JM
distance, it selects the three attributes that allow greater
discriminalidade between each class pair and performs
classification of them. For this paper, just the Maximum
Likelihood and Support Vector Machine classifiers were used, in a
single hierarchical level. The resulting classification is made by
taking classes that were more often identified by the classifier
within subsets of class pairs. The class pairs classifications
showed better separability when compared to a classification of
all classes at the same time. This result shall be studied to
prove its validity or if it is due to the inability to correctly
classify pixels belonging to classes not involved in pair
classification.",
conference-location = "Jo{\~a}o Pessoa",
conference-year = "25-29 abr. 2015",
isbn = "978-85-17-0076-8",
label = "585",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3JM4AGS",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4AGS",
targetfile = "p0585.pdf",
type = "Classifica{\c{c}}{\~a}o e minera{\c{c}}{\~a}o de dados",
urlaccessdate = "27 abr. 2024"
}