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@InProceedings{AdeuFerrAndrSant:2019:EvGrSe,
               author = "Adeu, Rodrigo S. S. and Ferreira, Karine Reis and Andrade, Pedro 
                         Ribeiro de and Santos, Lorena",
          affiliation = "Embraer and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Evaluating growing self-organizing maps for satellite image time 
                         series clustering",
            booktitle = "Anais... do 20º Simp{\'o}sio Brasileiro de Geoinform{\'a}tica",
                 year = "2019",
               editor = "Lisboa Filho, Jugurta and Monteiro, Antonio Miguel Vieira",
         organization = "Simp{\'o}sio Brasileiro de Geoinform{\'a}tica, 20. (GEOINFO)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "geoinformatica.",
             abstract = "In recent years, analysis of time series extracted from Earth 
                         observation satellite images has been widely used to produce land 
                         use and cover information. In time series analysis, clustering is 
                         a common technique performed to discover patterns on data sets. 
                         Self-Organizing Maps (SOM) neural network is a suitable method for 
                         such task. However, a critical limitation of SOM is that its map 
                         structure size must be predetermined. This limitation has been 
                         addressed by Growing SOM method. This paper presents an ongoing 
                         work on evaluating Growing SOM for Earth observation satellite 
                         image time series clustering.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos",
      conference-year = "11 -13 nov. 2019",
                 issn = "2179-4847",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGPDW34R/3UFECJL",
                  url = "http://urlib.net/ibi/8JMKD3MGPDW34R/3UFECJL",
           targetfile = "243-248.pdf",
        urlaccessdate = "28 mar. 2024"
}


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