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Artigo de periodico
Revisiting predictions of movie economic success: random Forest applied to profits (2023)
Souza, Thais Luiza Donega e ; Nishijima, Marislei ; Pires, Ricardo
Fonte: Multimedia Tools and Applications. Unidades: IRI, EACH
Assuntos: INDÚSTRIA CINEMATOGRÁFICA, PRODUÇÃO CINEMATOGRÁFICA, APRENDIZADO COMPUTACIONAL, SUCESSO NOS NEGÓCIOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUZA, Thais Luiza Donega e e NISHIJIMA, Marislei e PIRES, Ricardo. Revisiting predictions of movie economic success: random Forest applied to profits. Multimedia Tools and Applications, p. 1-24, 2023Tradução . . Disponível em: https://doi.org/10.1007/s11042-023-15169-4. Acesso em: 05 nov. 2024.
APA
Souza, T. L. D. e, Nishijima, M., & Pires, R. (2023). Revisiting predictions of movie economic success: random Forest applied to profits. Multimedia Tools and Applications, 1-24. doi:10.1007/s11042-023-15169-4
NLM
Souza TLD e, Nishijima M, Pires R. Revisiting predictions of movie economic success: random Forest applied to profits [Internet]. Multimedia Tools and Applications. 2023 ; 1-24.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/s11042-023-15169-4
Vancouver
Souza TLD e, Nishijima M, Pires R. Revisiting predictions of movie economic success: random Forest applied to profits [Internet]. Multimedia Tools and Applications. 2023 ; 1-24.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/s11042-023-15169-4
Artigo de periodico
Movie films consumption in Brazil: an analysis of Support Vector Machine classification (2019)
Nishijima, Marislei ; Nieuwenhoff, Nathalia; Pires, Ricardo; Oliveira, Patrícia Rufino
Fonte: AI & Society: journal of knowledge, culture and communication. Unidade: EACH
Assuntos: CINEMA, COMPORTAMENTO DO CONSUMIDOR, FILMES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NISHIJIMA, Marislei et al. Movie films consumption in Brazil: an analysis of Support Vector Machine classification. AI & Society: journal of knowledge, culture and communication, v. 34, n. 121, p. 01-07, 2019Tradução . . Disponível em: https://doi.org/10.1007/s00146-019-00899-7. Acesso em: 05 nov. 2024.
APA
Nishijima, M., Nieuwenhoff, N., Pires, R., & Oliveira, P. R. (2019). Movie films consumption in Brazil: an analysis of Support Vector Machine classification. AI & Society: journal of knowledge, culture and communication, 34( 121), 01-07. doi:10.1007/s00146-019-00899-7
NLM
Nishijima M, Nieuwenhoff N, Pires R, Oliveira PR. Movie films consumption in Brazil: an analysis of Support Vector Machine classification [Internet]. AI & Society: journal of knowledge, culture and communication. 2019 ; 34( 121): 01-07.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/s00146-019-00899-7
Vancouver
Nishijima M, Nieuwenhoff N, Pires R, Oliveira PR. Movie films consumption in Brazil: an analysis of Support Vector Machine classification [Internet]. AI & Society: journal of knowledge, culture and communication. 2019 ; 34( 121): 01-07.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/s00146-019-00899-7
Artigo de periodico
Movie flms consumption in Brazil: an analysis of support vector machine classifcation (2019)
Nishijima, Marislei ; Nieuwenhoff, Nathalia; Pires, Ricardo; Oliveira, Patrícia R.
Fonte: AI & Society: Journal of Knowledge, Culture and Communication. Unidades: IRI, EACH
Assuntos: CINEMA, CONSUMIDOR, DETERMINANTES, ANÁLISE DISCRIMINANTE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NISHIJIMA, Marislei et al. Movie flms consumption in Brazil: an analysis of support vector machine classifcation. AI & Society: Journal of Knowledge, Culture and Communication, 2019Tradução . . Disponível em: https://doi.org/10.1007/s00146-019-00899-7. Acesso em: 05 nov. 2024.
APA
Nishijima, M., Nieuwenhoff, N., Pires, R., & Oliveira, P. R. (2019). Movie flms consumption in Brazil: an analysis of support vector machine classifcation. AI & Society: Journal of Knowledge, Culture and Communication. doi:10.1007/s00146-019-00899-7
NLM
Nishijima M, Nieuwenhoff N, Pires R, Oliveira PR. Movie flms consumption in Brazil: an analysis of support vector machine classifcation [Internet]. AI & Society: Journal of Knowledge, Culture and Communication. 2019 ;[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/s00146-019-00899-7
Vancouver
Nishijima M, Nieuwenhoff N, Pires R, Oliveira PR. Movie flms consumption in Brazil: an analysis of support vector machine classifcation [Internet]. AI & Society: Journal of Knowledge, Culture and Communication. 2019 ;[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/s00146-019-00899-7
Artigo de periodico
Using a support-vector machine algorithm to classify lower extremity EMG signals during running shod/unshod with different foot strike patterns (2018)
Pires, Ricardo; Falcari, Thays; Campo, Alexandre B.; Pulcineli, Bárbara C.; Hamill, Joseph; Ervilha, Ulysses Fernandes
Fonte: Journal of Applied Biomechanics. Unidade: EACH
Assuntos: BIOMECÂNICA, CALÇADOS, CORRIDAS, RECONHECIMENTO DE PADRÕES, ELETROMIOGRAFIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PIRES, Ricardo et al. Using a support-vector machine algorithm to classify lower extremity EMG signals during running shod/unshod with different foot strike patterns. Journal of Applied Biomechanics, p. 01-15, 2018Tradução . . Disponível em: https://doi.org/10.1123/jab.2017-0349. Acesso em: 05 nov. 2024.
APA
Pires, R., Falcari, T., Campo, A. B., Pulcineli, B. C., Hamill, J., & Ervilha, U. F. (2018). Using a support-vector machine algorithm to classify lower extremity EMG signals during running shod/unshod with different foot strike patterns. Journal of Applied Biomechanics, 01-15. doi:10.1123/jab.2017-0349
NLM
Pires R, Falcari T, Campo AB, Pulcineli BC, Hamill J, Ervilha UF. Using a support-vector machine algorithm to classify lower extremity EMG signals during running shod/unshod with different foot strike patterns [Internet]. Journal of Applied Biomechanics. 2018 ; 01-15.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1123/jab.2017-0349
Vancouver
Pires R, Falcari T, Campo AB, Pulcineli BC, Hamill J, Ervilha UF. Using a support-vector machine algorithm to classify lower extremity EMG signals during running shod/unshod with different foot strike patterns [Internet]. Journal of Applied Biomechanics. 2018 ; 01-15.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1123/jab.2017-0349

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