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Artigo de periodico
Exploiting ergodicity of the logistic map using deep-zoom to improve security of chaos-based cryptosystems (2019)
Machicao, Jeaneth; Alves, Marcela; Baptista, Murilo S.; Bruno, Odemir Martinez
Fonte: International Journal of Modern Physics C. Unidade: IFSC
Assuntos: RECONHECIMENTO DE PADRÕES, PROCESSAMENTO DE IMAGENS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MACHICAO, Jeaneth et al. Exploiting ergodicity of the logistic map using deep-zoom to improve security of chaos-based cryptosystems. International Journal of Modern Physics C, v. 30, n. 4, p. 1950033-1-1950033-18, 2019Tradução . . Disponível em: https://doi.org/10.1142/S0129183119500335. Acesso em: 27 nov. 2025.
APA
Machicao, J., Alves, M., Baptista, M. S., & Bruno, O. M. (2019). Exploiting ergodicity of the logistic map using deep-zoom to improve security of chaos-based cryptosystems. International Journal of Modern Physics C, 30( 4), 1950033-1-1950033-18. doi:10.1142/S0129183119500335
NLM
Machicao J, Alves M, Baptista MS, Bruno OM. Exploiting ergodicity of the logistic map using deep-zoom to improve security of chaos-based cryptosystems [Internet]. International Journal of Modern Physics C. 2019 ; 30( 4): 1950033-1-1950033-18.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1142/S0129183119500335
Vancouver
Machicao J, Alves M, Baptista MS, Bruno OM. Exploiting ergodicity of the logistic map using deep-zoom to improve security of chaos-based cryptosystems [Internet]. International Journal of Modern Physics C. 2019 ; 30( 4): 1950033-1-1950033-18.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1142/S0129183119500335
Artigo de periodico
Enhancing LBP by preprocessing via anisotropic diffusion (2018)
Barros Neiva, Mariane; Guidotti, Patrick; Bruno, Odemir Martinez
Fonte: International Journal of Modern Physics C. Unidade: IFSC
Assuntos: RECONHECIMENTO DE PADRÕES, PROCESSAMENTO DE IMAGENS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BARROS NEIVA, Mariane e GUIDOTTI, Patrick e BRUNO, Odemir Martinez. Enhancing LBP by preprocessing via anisotropic diffusion. International Journal of Modern Physics C, v. 29, n. 8, p. 1850071-1-1850071-29, 2018Tradução . . Disponível em: https://doi.org/10.1142/S0129183118500717. Acesso em: 27 nov. 2025.
APA
Barros Neiva, M., Guidotti, P., & Bruno, O. M. (2018). Enhancing LBP by preprocessing via anisotropic diffusion. International Journal of Modern Physics C, 29( 8), 1850071-1-1850071-29. doi:10.1142/S0129183118500717
NLM
Barros Neiva M, Guidotti P, Bruno OM. Enhancing LBP by preprocessing via anisotropic diffusion [Internet]. International Journal of Modern Physics C. 2018 ; 29( 8): 1850071-1-1850071-29.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1142/S0129183118500717
Vancouver
Barros Neiva M, Guidotti P, Bruno OM. Enhancing LBP by preprocessing via anisotropic diffusion [Internet]. International Journal of Modern Physics C. 2018 ; 29( 8): 1850071-1-1850071-29.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1142/S0129183118500717
Parte de monografia/livro
Keygraphs: structured features for object detection and applications (2017)
Hashimoto, M; Morimitsu, Henrique; Hirata Júnior, Roberto ; César Júnior, Roberto Marcondes
Fonte: Pattern recognition and big data. Unidade: IME
Assuntos: VISÃO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HASHIMOTO, M et al. Keygraphs: structured features for object detection and applications. Pattern recognition and big data. Tradução . Singapore: Hackensack, NJ, 2017. . Disponível em: https://www.worldscientific.com/worldscibooks/10.1142/10153. Acesso em: 27 nov. 2025.
APA
Hashimoto, M., Morimitsu, H., Hirata Júnior, R., & César Júnior, R. M. (2017). Keygraphs: structured features for object detection and applications. In Pattern recognition and big data. Singapore: Hackensack, NJ. Recuperado de https://www.worldscientific.com/worldscibooks/10.1142/10153
NLM
Hashimoto M, Morimitsu H, Hirata Júnior R, César Júnior RM. Keygraphs: structured features for object detection and applications [Internet]. In: Pattern recognition and big data. Singapore: Hackensack, NJ; 2017. [citado 2025 nov. 27 ] Available from: https://www.worldscientific.com/worldscibooks/10.1142/10153
Vancouver
Hashimoto M, Morimitsu H, Hirata Júnior R, César Júnior RM. Keygraphs: structured features for object detection and applications [Internet]. In: Pattern recognition and big data. Singapore: Hackensack, NJ; 2017. [citado 2025 nov. 27 ] Available from: https://www.worldscientific.com/worldscibooks/10.1142/10153
Artigo de periodico
The dimension of ECOCs for multiclass classification problems (2008)
Pimenta, Edgar; Gama, João; Carvalho, André Carlos Ponce de Leon Ferreira de
Fonte: International Journal on Artificial Intelligence Tools. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PIMENTA, Edgar e GAMA, João e CARVALHO, André Carlos Ponce de Leon Ferreira de. The dimension of ECOCs for multiclass classification problems. International Journal on Artificial Intelligence Tools, v. 17, n. 3, p. 433-447, 2008Tradução . . Disponível em: https://doi.org/10.1142/S0218213008003984. Acesso em: 27 nov. 2025.
APA
Pimenta, E., Gama, J., & Carvalho, A. C. P. de L. F. de. (2008). The dimension of ECOCs for multiclass classification problems. International Journal on Artificial Intelligence Tools, 17( 3), 433-447. doi:10.1142/S0218213008003984
NLM
Pimenta E, Gama J, Carvalho ACP de LF de. The dimension of ECOCs for multiclass classification problems [Internet]. International Journal on Artificial Intelligence Tools. 2008 ; 17( 3): 433-447.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1142/S0218213008003984
Vancouver
Pimenta E, Gama J, Carvalho ACP de LF de. The dimension of ECOCs for multiclass classification problems [Internet]. International Journal on Artificial Intelligence Tools. 2008 ; 17( 3): 433-447.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1142/S0218213008003984

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