@InProceedings{AndradeJrArauSant:2015:AuCrMa,
               author = "Andrade Junior, Edemir Ferreira de and Araujo, Arnaldo de 
                         Albuquerque and Santos, Jefersson Alex dos",
          affiliation = "{Universidade Federal de Minas Gerais (UFMG)} and {Universidade 
                         Federal de Minas Gerais (UFMG)} and {Universidade Federal de Minas 
                         Gerais (UFMG)}",
                title = "Automatic Creation of Maps by Using Multiple Data Sensors",
            booktitle = "Proceedings...",
                 year = "2015",
               editor = "Rios, Ricardo Araujo and Paiva, Afonso",
         organization = "Conference on Graphics, Patterns and Images, 28. (SIBGRAPI)",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "Data fusion, remote sensing, ensemble of classifiers, mapping.",
             abstract = "An usual way to acquire information about monitored objects or 
                         areas in earth surface is by using remote sensing images. These 
                         images can be obtained by different types of sensors (e.g active 
                         and passive) and according to the sensor, distinct properties can 
                         be observed from the specified data. Typically, these sensor are 
                         specialized to encode one or few properties from the object (e.g. 
                         spectral and spatial properties), which makes necessary the 
                         utilization of diverse and different sensors to obtain many 
                         complementary information as possible. Given the amount of 
                         information collected, is essential use a capable technique to 
                         combine accordingly the different characteristics obtained. The 
                         objective of this work, which is in progress, is the development 
                         of a framework able to exploit the diversity of these different 
                         types of features, extracted from different sensors, to achieve 
                         high degrees of accuracy in the creation of thematic maps for the 
                         classification task.",
  conference-location = "Salvador, BA, Brazil",
      conference-year = "26-29 Aug. 2015",
             language = "en",
                  ibi = "8JMKD3MGPBW34M/3JS3Q42",
                  url = "http://urlib.net/ibi/8JMKD3MGPBW34M/3JS3Q42",
           targetfile = "ferreira_wip_sibgrapi2014_cameraready.pdf",
        urlaccessdate = "2024, May 02"
}