@InProceedings{SantosVentMachLipo:1996:ApNeNe,
               author = "Santos, Joao Roberto dos and Venturieri, Adriano and Machado, 
                         Ricardo Jose and Liporace, Frederico dos Santos",
                title = "Applicability of neural network architecture by a fuzzy model to 
                         identify natural vegetation regrowth in Brazilian Amazonia",
                 year = "1996",
                pages = "204--208",
         organization = "International Congress for Photogrammetry and Remote Sensing, 
                         18.",
             keywords = "VEGETACAO, AMAZONIA (REGIAO), MONITORAMENTO, REDES NEURAIS, 
                         SEGMENTACAO, MAPEADOR TEMATICO (LANDSAT), MONITORING, VEGETATION, 
                         SEGMENTATION, REGROWTH, THEMATIC MAPPER (LANDSAT).",
             abstract = "The objetive of this study is to present the results of 
                         preparation of a neural network trained by a backpropagation 
                         algorithm, in order to process TM-Landsat images, used to identify 
                         areas under secondary succession, among other landuse classes in 
                         Amazonia. Image segmentation techniques by an algorithm of region 
                         growth and labelling of these segments by fuzzy-logic were also 
                         used for the preparation of the start-up network. The performance 
                         of the network to delineate the {"}initial{"} and {"}advanced{"} 
                         regrowth areas, was obtained using both sensitivity and 
                         specificity indices and of the MSE (Mean Square Error). Generally, 
                         it appears that both spectral, textural (entropy and 
                         correlation)and contextual descriptors are effective for the 
                         identification of regrowth areas in Amazonia.",
  conference-location = "Viena, AU",
      conference-year = "09-19 July 1996",
                label = "7859",
         organisation = "ISPRS",
           targetfile = "1996_santos.pdf",
        urlaccessdate = "21 maio 2024"
}