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Artigo de periodico
Visual feature fusion and its application to support unsupervised clustering tasks (2020)
Hilasaca, Gladys Marleny ; Paulovich, Fernando Vieira
Source: Information Visualization. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, ALGORITMOS ÚTEIS E ESPECÍFICOS, VISUALIZAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HILASACA, Gladys Marleny e PAULOVICH, Fernando Vieira. Visual feature fusion and its application to support unsupervised clustering tasks. Information Visualization, v. 19, n. 2, p. 163-179, 2020Tradução . . Disponível em: https://doi.org/10.1177/1473871619891062. Acesso em: 12 nov. 2025.
APA
Hilasaca, G. M., & Paulovich, F. V. (2020). Visual feature fusion and its application to support unsupervised clustering tasks. Information Visualization, 19( 2), 163-179. doi:10.1177/1473871619891062
NLM
Hilasaca GM, Paulovich FV. Visual feature fusion and its application to support unsupervised clustering tasks [Internet]. Information Visualization. 2020 ; 19( 2): 163-179.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1177/1473871619891062
Vancouver
Hilasaca GM, Paulovich FV. Visual feature fusion and its application to support unsupervised clustering tasks [Internet]. Information Visualization. 2020 ; 19( 2): 163-179.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1177/1473871619891062
Artigo de periodico
Visualization in the preprocessing phase: getting insights from enterprise professionals (2020)
Milani, Alessandra Maciel Paz ; Paulovich, Fernando Vieira ; Manssour, Isabel Harb
Source: Information Visualization. Unidade: ICMC
Subjects: VISUALIZAÇÃO, MINERAÇÃO DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MILANI, Alessandra Maciel Paz e PAULOVICH, Fernando Vieira e MANSSOUR, Isabel Harb. Visualization in the preprocessing phase: getting insights from enterprise professionals. Information Visualization, v. 19, n. 4, p. 273-287, 2020Tradução . . Disponível em: https://doi.org/10.1177/1473871619896101. Acesso em: 12 nov. 2025.
APA
Milani, A. M. P., Paulovich, F. V., & Manssour, I. H. (2020). Visualization in the preprocessing phase: getting insights from enterprise professionals. Information Visualization, 19( 4), 273-287. doi:10.1177/1473871619896101
NLM
Milani AMP, Paulovich FV, Manssour IH. Visualization in the preprocessing phase: getting insights from enterprise professionals [Internet]. Information Visualization. 2020 ; 19( 4): 273-287.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1177/1473871619896101
Vancouver
Milani AMP, Paulovich FV, Manssour IH. Visualization in the preprocessing phase: getting insights from enterprise professionals [Internet]. Information Visualization. 2020 ; 19( 4): 273-287.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1177/1473871619896101
Artigo de periodico
Deep learning multidimensional projections (2020)
Espadoto, Mateus ; Hirata, Nina Sumiko Tomita ; Telea, Alexandru Cristian
Source: Information Visualization. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, APRENDIZAGEM PROFUNDA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ESPADOTO, Mateus e HIRATA, Nina Sumiko Tomita e TELEA, Alexandru Cristian. Deep learning multidimensional projections. Information Visualization, v. 19, n. 3, p. 247-269, 2020Tradução . . Disponível em: https://doi.org/10.1177/1473871620909485. Acesso em: 12 nov. 2025.
APA
Espadoto, M., Hirata, N. S. T., & Telea, A. C. (2020). Deep learning multidimensional projections. Information Visualization, 19( 3), 247-269. doi:10.1177/1473871620909485
NLM
Espadoto M, Hirata NST, Telea AC. Deep learning multidimensional projections [Internet]. Information Visualization. 2020 ; 19( 3): 247-269.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1177/1473871620909485
Vancouver
Espadoto M, Hirata NST, Telea AC. Deep learning multidimensional projections [Internet]. Information Visualization. 2020 ; 19( 3): 247-269.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1177/1473871620909485

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