@InProceedings{LacerdaShiDamAnjHab:2020:AnVHIm,
               author = "Lacerda, M. G. and Shiguemori, Elcio Hideiti and Dami{\~a}o, A. 
                         J. and Anjos, C. S. and Habermann, M.",
          affiliation = "{Instituto de Estudos Avan{\c{c}}ados (IEAv)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto de Estudos 
                         Avan{\c{c}}ados (IEAv)} and {Instituto Federal de Ci{\^e}ncia e 
                         Tecnologia do Sul de Minas (IFSULDEMINAS)} and {Instituto de 
                         Estudos Avan{\c{c}}ados (IEAv)}",
                title = "Analysis of VHR image classification by single and ensemble of 
                         classifiers",
            booktitle = "Proceedings...",
                 year = "2020",
                pages = "126--131",
         organization = "IEEE Latin American GRSS; ISPRS Remote Sensing Conference",
            publisher = "IEEE",
             keywords = "RPAS, Very High Resolution Images, Classifiers, Majority Voting, 
                         Computational Time.",
             abstract = "Given the wide variety of image classifiers available nowadays, 
                         some questions remain about the accuracy and processing time of 
                         Very High Resolution (VHR) images. Another question concerns the 
                         use of a Single or Ensemble Classifiers. Of course, the main 
                         factor to consider is the quality of the classified image, but 
                         computational cost is also important, especially in applications 
                         that require real-time processing. Given this scenario, this paper 
                         aims to relate the accuracy of seven single classifiers and the 
                         ensemble of the same classifiers with the processing time. In this 
                         paper the ensemble of classifiers had the best results in terms of 
                         accuracy, however, it comes to processing time, the decision tree 
                         had the best performance.",
  conference-location = "Santiago, Chile",
      conference-year = "21-26 Mar.",
                  doi = "10.1109/LAGIRS48042.2020.9165637",
                  url = "http://dx.doi.org/10.1109/LAGIRS48042.2020.9165637",
                 isbn = "978-172814350-7",
             language = "en",
           targetfile = "lacerda_analysis.pdf",
        urlaccessdate = "28 abr. 2024"
}