Time series classification using motifs and characteristics extraction: a case study on ECG databases (2013)
- Authors:
- USP affiliated authors: BATISTA, GUSTAVO ENRIQUE DE ALMEIDA PRADO ALVES - ICMC ; REZENDE, SOLANGE OLIVEIRA - ICMC
- Unidade: ICMC
- DOI: 10.2991/.2013.40
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Publisher: Atlantis Press
- Publisher place: Paris
- Date published: 2013
- ISBN: 9789491216985
- Source:
- Título do periódico: Proceedings
- Conference titles: International Workshop on Knowledge Discovery, Knowledge Management and Decision Support - Eureka
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by-nc
-
ABNT
MALETZKE, André G et al. Time series classification using motifs and characteristics extraction: a case study on ECG databases. 2013, Anais.. Paris: Atlantis Press, 2013. Disponível em: https://doi.org/10.2991/.2013.40. Acesso em: 24 abr. 2024. -
APA
Maletzke, A. G., Lee, H. D., Batista, G. E. de A. P. A., Rezende, S. O., Machado, R. B., Voltolini, R. F., et al. (2013). Time series classification using motifs and characteristics extraction: a case study on ECG databases. In Proceedings. Paris: Atlantis Press. doi:10.2991/.2013.40 -
NLM
Maletzke AG, Lee HD, Batista GE de APA, Rezende SO, Machado RB, Voltolini RF, Maciel JN, Silva F, Santos LB dos, Wu FC. Time series classification using motifs and characteristics extraction: a case study on ECG databases [Internet]. Proceedings. 2013 ;[citado 2024 abr. 24 ] Available from: https://doi.org/10.2991/.2013.40 -
Vancouver
Maletzke AG, Lee HD, Batista GE de APA, Rezende SO, Machado RB, Voltolini RF, Maciel JN, Silva F, Santos LB dos, Wu FC. Time series classification using motifs and characteristics extraction: a case study on ECG databases [Internet]. Proceedings. 2013 ;[citado 2024 abr. 24 ] Available from: https://doi.org/10.2991/.2013.40 - Music classification by transductive learning using bipartite heterogeneous networks
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Informações sobre o DOI: 10.2991/.2013.40 (Fonte: oaDOI API)
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