@InProceedings{Reis:2013:CoClMá,
               author = "Reis, Mariane Souza",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Compara{\c{c}}{\~a}o entre os Classificadores M{\'a}xima 
                         Verossimilhan{\c{c}}a, SVM e Rede Neural MLP para Uso e Cobertura 
                         da Terra em Parcela da FLONA Tapaj{\'o}s e Arredores",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "2377--2383",
         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 = "The available tools to classify an image has grown in the last 
                         years, with the development of more efficient algorithms and 
                         computer technology. This paper aims to evaluate the performance 
                         of two supervised classifiers using different parameters, Support 
                         Vector Machine and MLP based Neural Net, when compared with 
                         Maximum likelihood, on an image from Landsat5 satellites sensor 
                         Tematic Mapper. The study area is located in a parcel and 
                         surroundings of Floresta Nacional do Tapaj{\'o}s, in which there 
                         is forest in different stages, new and old regeneration and 
                         agriculture. The respective Kappa coefficient was validated using 
                         an hypothesis test with 5% of significance. It was defined six 
                         classes of land use and land cover associated with Primary Forest 
                         and Primary Forest in Exploration, Degraded Forest, Old 
                         Regeneration and Intermediate Regeneration, Initial Regeneration, 
                         Prepared Soil for Agriculture and Soybean with 100 days from 
                         sowing, Pasture and Soybean with 40 days from sowing. Although SVM 
                         has showed good results, it was statistically similar to maximum 
                         likelihood. Neural Network has showed statistically inferior or 
                         equal results, bus demanded more time, process capacity and is 
                         more difficult, due the necessity to choose more parameters. It 
                         was concluded that future investigations are needed to achieve the 
                         optimum classification using the chosen algorithms.",
  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 = "1545",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GM37",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GM37",
           targetfile = "p1545.pdf",
                 type = "Classifica{\c{c}}{\~a}o e Minera{\c{c}}{\~a}o de Dados",
        urlaccessdate = "12 maio 2024"
}