Source: Scientific Programme. Conference titles: International Symposium on Recurrence Plots. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS
ABNT
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: 24 maio 2024.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 2024 maio 24 ] 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 2024 maio 24 ] Available from: http://symposium.recurrence-plot.tk/programme2017.pdf