Source: Brazilian Journal of Geology. Unidades: IEE, IGC
Assunto: MUDANÇA CLIMÁTICA
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DIAS, Helen Cristina et al. Landslide recognition using SVM, Random Forest, and Maximum Likelihood classifiers on high-resolution satellite images: A case study of Itaóca, southeastern Brazil. Brazilian Journal of Geology, v. 51, n. 4. p. e20200105/1-10, 2021Tradução . . Disponível em: https://www.scielo.br/j/bjgeo/a/Y6s5whm57BV9cgrMDWcJvgp/?format=pdf&lang=en. Acesso em: 07 set. 2024.APA
Dias, H. C., Sandre, L. H., Satizábal Alarcón, D. A., Grohmann, C. H., & Quintanilha, J. A. (2021). Landslide recognition using SVM, Random Forest, and Maximum Likelihood classifiers on high-resolution satellite images: A case study of Itaóca, southeastern Brazil. Brazilian Journal of Geology, 51( 4. p. e20200105/1-10). Recuperado de https://www.scielo.br/j/bjgeo/a/Y6s5whm57BV9cgrMDWcJvgp/?format=pdf&lang=enNLM
Dias HC, Sandre LH, Satizábal Alarcón DA, Grohmann CH, Quintanilha JA. Landslide recognition using SVM, Random Forest, and Maximum Likelihood classifiers on high-resolution satellite images: A case study of Itaóca, southeastern Brazil [Internet]. Brazilian Journal of Geology. 2021 ; 51( 4. p. e20200105/1-10):[citado 2024 set. 07 ] Available from: https://www.scielo.br/j/bjgeo/a/Y6s5whm57BV9cgrMDWcJvgp/?format=pdf&lang=enVancouver
Dias HC, Sandre LH, Satizábal Alarcón DA, Grohmann CH, Quintanilha JA. Landslide recognition using SVM, Random Forest, and Maximum Likelihood classifiers on high-resolution satellite images: A case study of Itaóca, southeastern Brazil [Internet]. Brazilian Journal of Geology. 2021 ; 51( 4. p. e20200105/1-10):[citado 2024 set. 07 ] Available from: https://www.scielo.br/j/bjgeo/a/Y6s5whm57BV9cgrMDWcJvgp/?format=pdf&lang=en