@InProceedings{NegriDutrSant:2012:SuVeMa,
               author = "Negri, Rog{\'e}rio Galante and Dutra, Luciano Vieira and 
                         Sant'Anna, Sidinei Jo{\~a}o Siqueira",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Support Vector Machine and Bathacharrya Kernel Function for Region 
                         Based Classification",
            booktitle = "Proceedings...",
                 year = "2012",
         organization = "IEEE International Geoscience and Remote Sensing Symposium, 32. 
                         (IGARSS).",
             keywords = "Region Based Classification, Support Vector Machine, Stochastic 
                         Distance, Bhattacharyya Kernel Function.",
             abstract = "Region based methods are indicated to classify image with strong 
                         heterogeneity, where only the spectral information is not enough. 
                         Different approaches have been proposed to perform this kind of 
                         classification. This study presents a new approach for region 
                         based classification that consists in use the Support Vector 
                         Machine (SVM) method with Bhattacharyya kernel function. A high 
                         resolution IKONOS image was classified. The classification results 
                         shows that SVM method using the Bhattacharyya kernel is better 
                         than Minimum Distance Classifier and conventional SVM.",
  conference-location = "Munich",
      conference-year = "2012",
                label = "lattes: 8201805132981288 1 NegriDutrSant:2012:SuVeMa",
             language = "en",
           targetfile = "negri_support.pdf",
        urlaccessdate = "30 abr. 2024"
}