@InProceedings{BarbosaNomaKortFons:2015:EsExCl,
               author = "Barbosa, David Pereira and Noma, Alexandre and Korting, Thales 
                         Sehn and Fonseca, Leila Maria Garcia",
          affiliation = "{} and {} and {Instituto Nacional de Pesquisas Espaciais (INPE)} 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Um Estudo Experimental com Classificadores baseados em 
                         Regi{\~o}es e Perfis EVI",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "880--887",
         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 = "INPE is responsible for several projects, including PRODES and 
                         TerraClass. Basically, PRODES provides annual maps corresponding 
                         to annual deforestation in Amazonia Based on a deforestation map, 
                         TerraClass provides a classification map for the deforested areas: 
                         agriculture, pasture, forest, hydrography, urban, etc. In order to 
                         build a classification map, manual classification is a cumbersome 
                         and tedious work. In this sense, automatic or semi-automatic 
                         approaches are highly desirable for classification of the 
                         deforested areas. Previous work compared different approaches by 
                         using TerraClass data from 2008 for binary classification: 
                         agriculture and non-agriculture.The present paper extends the 
                         previous work in three aspects: (1) by including recent TerraClass 
                         data from 2010; (2) by treating the multiclass case by considering 
                         3 or more classes; and (3) by considering an additional boosting 
                         approach for classification. Specifically, SVM, OPF, Naive Bayes, 
                         Decision Tree, Nearest Neighbors and a boosting technique are 
                         compared by following a k-fold cross validation.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "169",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM47GK",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM47GK",
           targetfile = "p0169.pdf",
                 type = "Classifica{\c{c}}{\~a}o e minera{\c{c}}{\~a}o de dados",
        urlaccessdate = "27 abr. 2024"
}