author = "Borges, D{\'{\i}}bio Leandro and Orr, Mark J. and Fisher, Robert 
          affiliation = "{Department of Artificial Intelligence of Edinburgh University} 
                         and {Centre for Cognitive Science of Edinburgh University} and 
                         {Centre for Cognitive Science of Edinburgh University}",
                title = "A radial basis function neural network for parts identification of 
                         three dimensional shapes",
            booktitle = "Anais...",
                 year = "1994",
               editor = "Freitas, Carla dal Sasso and Geus, Klaus de and Scheer, 
                pages = "77--84",
         organization = "Simp{\'o}sio Brasileiro de Computa{\c{c}}{\~a}o Gr{\'a}fica e 
                         Processamento de Imagens, 7. (SIBGRAPI)",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "function neural, function neural, image understanding.",
             abstract = "This discrimination of volumetric pieces or parts of objects from 
                         range data is one key element for achieving 3-D object 
                         recognition. In this paper it is shown that previously segmented 
                         and acquired super quadrics from range data can be reliably mapped 
                         into a set of qualitative volumetric shapes (geons) by means of an 
                         RBF (Radial Basis Function) neural network classifier. We use a 
                         regularized RBF classifier and the results are shown to be both 
                         reliable and efficient in the context of range image 
  conference-location = "Curitiba",
      conference-year = "9 - 11 nov. 1994",
                 isbn = "978-85-7669-272-0",
             language = "en",
                  ibi = "8JMKD3MGPBW34M/3DDQLDL",
                  url = "",
           targetfile = "11 A radial basis function neural network.pdf",
                 type = "Vis{\~a}o Computacional",
               volume = "1",
        urlaccessdate = "2021, Dec. 08"