@InProceedings{AbdallaVolo:2013:EsCoDi,
               author = "Abdalla, Livia dos Santos and Volot{\~a}o, Carlos Frederico de 
                         S{\'a}",
                title = "Estudo da configura{\c{c}}{\~a}o de diferentes arquiteturas de 
                         redes neurais artificiais MLP para classifica{\c{c}}{\~a}o de 
                         imagens {\'o}pticas",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "8200--8207",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 16. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Artificial neural networks (ANN) can be used to produce several 
                         products, including remote sensing classification images. ANN may 
                         not beat the performance of traditional classification methods, 
                         but it is unique in the sense that: 1) it is not dependent on the 
                         prior knowledge of statistical model of data; and 2) it makes it 
                         possible to add unusual information by the configuration of 
                         parameters, input, hidden and output layers. Motivated by the 
                         ability to add different levels of information, including spatial 
                         and non-spatial data (e.g., Digital Terrain Models, time, date, a 
                         given classification or a segmented image), and comparing to 
                         classical methods of classification, this work test the use of ANN 
                         for image classification. Despite this capability, this work aims 
                         to compare the plain classification ability, by means of kappa 
                         values and training sets as a reference example when there is no 
                         ground truth available. Providing a fare alternative for image 
                         classification, the advantages of the potential enhancements are 
                         to be studied in future papers. This study explores simple 
                         architectures of MLP to identify common themes of land cover and 
                         uses, and is based on HRG/SPOT5 images. The results using kappa 
                         was 91% indicating that the RNA has achieved a good index of 
                         training.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "13-18 abr. 2013",
                 isbn = "{978-85-17-00066-9 (Internet)} and {978-85-17-00065-2 (DVD)}",
                label = "1102",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GJ5D",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GJ5D",
           targetfile = "p1102.pdf",
                 type = "Processamento de Imagens",
        urlaccessdate = "11 maio 2024"
}