Fonte: Scientific Programme. Nome do evento: International Symposium on Recurrence Plots. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS
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PAGLIOSA, Lucas e MELLO, Rodrigo Fernandes de. Using cross-recurrence quantification analysis to improve semi-supervised time series classification of positive and unlabeled problems. 2017, Anais.. São Paulo: Poli/USP, 2017. Disponível em: http://symposium.recurrence-plot.tk/programme2017.pdf. Acesso em: 09 nov. 2025.APA
Pagliosa, L., & Mello, R. F. de. (2017). Using cross-recurrence quantification analysis to improve semi-supervised time series classification of positive and unlabeled problems. In Scientific Programme. São Paulo: Poli/USP. Recuperado de http://symposium.recurrence-plot.tk/programme2017.pdfNLM
Pagliosa L, Mello RF de. Using cross-recurrence quantification analysis to improve semi-supervised time series classification of positive and unlabeled problems [Internet]. Scientific Programme. 2017 ;[citado 2025 nov. 09 ] Available from: http://symposium.recurrence-plot.tk/programme2017.pdfVancouver
Pagliosa L, Mello RF de. Using cross-recurrence quantification analysis to improve semi-supervised time series classification of positive and unlabeled problems [Internet]. Scientific Programme. 2017 ;[citado 2025 nov. 09 ] Available from: http://symposium.recurrence-plot.tk/programme2017.pdf
