Source: Pattern Recognition. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, ANÁLISE DE SÉRIES TEMPORAIS
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PAGLIOSA, Lucas de Carvalho e MELLO, Rodrigo Fernandes de. Semi-supervised time series classification on positive and unlabeled problems using cross-recurrence quantification analysis. Pattern Recognition, v. 80, p. 53-63, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.patcog.2018.02.030. Acesso em: 11 nov. 2025.APA
Pagliosa, L. de C., & Mello, R. F. de. (2018). Semi-supervised time series classification on positive and unlabeled problems using cross-recurrence quantification analysis. Pattern Recognition, 80, 53-63. doi:10.1016/j.patcog.2018.02.030NLM
Pagliosa L de C, Mello RF de. Semi-supervised time series classification on positive and unlabeled problems using cross-recurrence quantification analysis [Internet]. Pattern Recognition. 2018 ; 80 53-63.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2018.02.030Vancouver
Pagliosa L de C, Mello RF de. Semi-supervised time series classification on positive and unlabeled problems using cross-recurrence quantification analysis [Internet]. Pattern Recognition. 2018 ; 80 53-63.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2018.02.030
