Fonte: Journal of Physics: Complexity. Unidades: ICMC, IFSC
Assuntos: VISÃO COMPUTACIONAL, APRENDIZADO COMPUTACIONAL, TOPOLOGIA EM COMPUTAÇÃO, REDES NEURAIS, TEORIA DOS GRAFOS, CÓRTEX CEREBRAL (ANÁLISE), CÉREBRO (ANÁLISE;ESTUDO)
ABNT
ALVES, Caroline Lourenço et al. On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments. Journal of Physics: Complexity, v. 5, n. Ja 2024, p. 015002-1-015002-23, 2024Tradução . . Disponível em: https://doi.org/10.1088/2632-072X/ad1c68. Acesso em: 23 ago. 2024.APA
Alves, C. L., Ciba, M., Toutain, T. G. L. de, Porto, J. A. M., Sena, E. P. de, Thielemann, C., & Rodrigues, F. (2024). On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments. Journal of Physics: Complexity, 5( Ja 2024), 015002-1-015002-23. doi:10.1088/2632-072X/ad1c68NLM
Alves CL, Ciba M, Toutain TGL de, Porto JAM, Sena EP de, Thielemann C, Rodrigues F. On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments [Internet]. Journal of Physics: Complexity. 2024 ; 5( Ja 2024): 015002-1-015002-23.[citado 2024 ago. 23 ] Available from: https://doi.org/10.1088/2632-072X/ad1c68Vancouver
Alves CL, Ciba M, Toutain TGL de, Porto JAM, Sena EP de, Thielemann C, Rodrigues F. On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments [Internet]. Journal of Physics: Complexity. 2024 ; 5( Ja 2024): 015002-1-015002-23.[citado 2024 ago. 23 ] Available from: https://doi.org/10.1088/2632-072X/ad1c68