Analysis of radiographic images of patients with COVID-19 using fractal dimension and complex network-based high-level classification (2021)
- Authors:
- Autor USP: LIANG, ZHAO - FFCLRP
- Unidade: FFCLRP
- DOI: 10.1007/978-3-030-93409-5_2
- Subjects: COVID-19; REDES COMPLEXAS; RADIOGRAFIA; DIMENSÃO; RAIOS X; IMAGEM DIGITAL
- Keywords: Fractal dimension; Complexity; High-level classification; Complex networks
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Studies in Computational Intelligence
- ISSN: 1860-9503
- Volume/Número/Paginação/Ano: v. 1015, p. 16-26, 2021
- Conference titles: International Conference on Complex Networks and Their Applications
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
LIU, Weiguang et al. Analysis of radiographic images of patients with COVID-19 using fractal dimension and complex network-based high-level classification. Studies in Computational Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-93409-5_2. Acesso em: 28 fev. 2026. , 2021 -
APA
Liu, W., Yan, J., Zhu, Y. -tao, Pereira, E. J. de F., Li, G., Zheng, Q., & Liang, Z. (2021). Analysis of radiographic images of patients with COVID-19 using fractal dimension and complex network-based high-level classification. Studies in Computational Intelligence. Cham: Springer. doi:10.1007/978-3-030-93409-5_2 -
NLM
Liu W, Yan J, Zhu Y-tao, Pereira EJ de F, Li G, Zheng Q, Liang Z. Analysis of radiographic images of patients with COVID-19 using fractal dimension and complex network-based high-level classification [Internet]. Studies in Computational Intelligence. 2021 ; 1015 16-26.[citado 2026 fev. 28 ] Available from: https://doi.org/10.1007/978-3-030-93409-5_2 -
Vancouver
Liu W, Yan J, Zhu Y-tao, Pereira EJ de F, Li G, Zheng Q, Liang Z. Analysis of radiographic images of patients with COVID-19 using fractal dimension and complex network-based high-level classification [Internet]. Studies in Computational Intelligence. 2021 ; 1015 16-26.[citado 2026 fev. 28 ] Available from: https://doi.org/10.1007/978-3-030-93409-5_2 - Semi-supervised learning with concept drift using particle dynamics applied to network intrusion detection data
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Informações sobre o DOI: 10.1007/978-3-030-93409-5_2 (Fonte: oaDOI API)
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