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@InProceedings{NegriDutrSant:2015:PrMeAv,
               author = "Negri, Rog{\'e}rio Galante and Dutra, Luciano Vieira and 
                         Sant'Anna, Sidnei Jo{\~a}o Siqueira",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Proposta de uma medida para avalia{\c{c}}{\~a}o de 
                         classifica{\c{c}}{\~a}o em bordas",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "3431--3438",
         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 = "An important step made after obtain image classification results 
                         is the accuracy assessment. The accuracy assessment has been 
                         intensively studied by researchers in remote sensing. Usually, 
                         these measures are computed with basis on samples distributed over 
                         the image, within well defined regions and a priori known. This 
                         paper proposes a new measure for classification assessment over 
                         edges of objects. A case study about the land use and cover 
                         classification on an Amazon region adopting an ALOS-PALSAR image 
                         and Support Vector Machine was performed. The results show that 
                         the use of this new measure together the Kappa coefficient can 
                         provide a more robust analysis regarding the classification 
                         results.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "678",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4BMC",
                  url = "http://urlib.net/rep/8JMKD3MGP6W34M/3JM4BMC",
           targetfile = "p0678.pdf",
                 type = "Classifica{\c{c}}{\~a}o e minera{\c{c}}{\~a}o de dados",
        urlaccessdate = "02 dez. 2020"
}


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