ReP USP - Resultado da busca

Trabalho de evento
High-level classification for EEG analysis (2023)
Carneiro, Murillo Guimarães; Ramos, Camila D.; Destro Filho, João Batista; Zhu, Yu-tao; Ji, Donghong; Liang, Zhao
Conference titles: International Joint Conference on Neural Networks. Unidade: FFCLRP
Subjects: REDES COMPLEXAS, SISTEMA BINÁRIO, ELETROENCEFALOGRAFIA, PROGNÓSTICO, COMA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CARNEIRO, Murillo Guimarães et al. High-level classification for EEG analysis. 2023, Anais.. Queensland: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 2023. p. 1-8. Disponível em: https://doi.org/10.1109/IJCNN54540.2023.10191823. Acesso em: 01 nov. 2024.
APA
Carneiro, M. G., Ramos, C. D., Destro Filho, J. B., Zhu, Y. -tao, Ji, D., & Liang, Z. (2023). High-level classification for EEG analysis. In (p. 1-8). Queensland: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.1109/IJCNN54540.2023.10191823
NLM
Carneiro MG, Ramos CD, Destro Filho JB, Zhu Y-tao, Ji D, Liang Z. High-level classification for EEG analysis [Internet]. 2023 ; 1-8.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191823
Vancouver
Carneiro MG, Ramos CD, Destro Filho JB, Zhu Y-tao, Ji D, Liang Z. High-level classification for EEG analysis [Internet]. 2023 ; 1-8.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191823
Trabalho de evento-anais periodico
Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach (2023)
Zuñiga, Esteban Wilfredo Vilca ; Ranieri, Caetano Mazzoni ; Zhao, Liang ; Ueyama, Jó ; Zhu, Yu-tao; Ji, Donghong
Source: Proceedings. Conference titles: International Neural Network Society Workshop on Deep Learning Innovations and Applications - INNS DLIA. Unidades: FFCLRP, ICMC
Subjects: DINHEIRO ELETRÔNICO, APRENDIZAGEM PROFUNDA, REDES COMPLEXAS, INVESTIMENTOS, LUCRO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ZUÑIGA, Esteban Wilfredo Vilca et al. Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach. Proceedings. Amsterdam: Elsevier. Disponível em: https://doi.org/10.1016/j.procs.2023.08.192. Acesso em: 01 nov. 2024. , 2023
APA
Zuñiga, E. W. V., Ranieri, C. M., Zhao, L., Ueyama, J., Zhu, Y. -tao, & Ji, D. (2023). Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach. Proceedings. Amsterdam: Elsevier. doi:10.1016/j.procs.2023.08.192
NLM
Zuñiga EWV, Ranieri CM, Zhao L, Ueyama J, Zhu Y-tao, Ji D. Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach [Internet]. Proceedings. 2023 ; 222 539-548.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.procs.2023.08.192
Vancouver
Zuñiga EWV, Ranieri CM, Zhao L, Ueyama J, Zhu Y-tao, Ji D. Maximizing portfolio profitability during a cryptocurrency downtrend: a bitcoin blockchain transaction-based approach [Internet]. Proceedings. 2023 ; 222 539-548.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.procs.2023.08.192
Trabalho de evento-anais periodico
Classification of dispersed patterns of radiographic images with COVID-19 by core-periphery network modeling (2021)
Yan, Jianglong; Liu, Weiguang; Zhu, Yu-tao; Li, Gen; Zheng, Qiusheng; Liang, Zhao
Source: Complex Networks & Their Applications X. Conference titles: International Conference on Complex Networks and Their Applications. Unidade: FFCLRP
Subjects: COVID-19, RAIOS X, IMAGEM DIGITAL, DADOS CATEGORIZADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
YAN, Jianglong et al. Classification of dispersed patterns of radiographic images with COVID-19 by core-periphery network modeling. Complex Networks & Their Applications X. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-93409-5_4. Acesso em: 01 nov. 2024. , 2021
APA
Yan, J., Liu, W., Zhu, Y. -tao, Li, G., Zheng, Q., & Liang, Z. (2021). Classification of dispersed patterns of radiographic images with COVID-19 by core-periphery network modeling. Complex Networks & Their Applications X. Cham: Springer. doi:10.1007/978-3-030-93409-5_4
NLM
Yan J, Liu W, Zhu Y-tao, Li G, Zheng Q, Liang Z. Classification of dispersed patterns of radiographic images with COVID-19 by core-periphery network modeling [Internet]. Complex Networks & Their Applications X. 2021 ; 1 40-49.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/978-3-030-93409-5_4
Vancouver
Yan J, Liu W, Zhu Y-tao, Li G, Zheng Q, Liang Z. Classification of dispersed patterns of radiographic images with COVID-19 by core-periphery network modeling [Internet]. Complex Networks & Their Applications X. 2021 ; 1 40-49.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/978-3-030-93409-5_4
Trabalho de evento-anais periodico
Analysis of radiographic images of patients with COVID-19 using fractal dimension and complex network-based high-level classification (2021)
Liu, Weiguang; Yan, Jianglong; Zhu, Yu-tao; Pereira, Everson José de Freitas; Li, Gen; Zheng, Qiusheng; Liang, Zhao
Source: Studies in Computational Intelligence. Conference titles: International Conference on Complex Networks and Their Applications. Unidade: FFCLRP
Subjects: COVID-19, REDES COMPLEXAS, RADIOGRAFIA, DIMENSÃO, RAIOS X, IMAGEM DIGITAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 01 nov. 2024. , 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 2024 nov. 01 ] 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 2024 nov. 01 ] Available from: https://doi.org/10.1007/978-3-030-93409-5_2

USP Schools

ReP

Filtros

Authors

Subjects

Funding Agencies

Non normalized affiliation