ReP USP - Resultado da busca

Filtros : "Communications in Computer and Information Science" "Latin American Workshop on Computational Neuroscience - LAWCN" Limpar

Filtros

USP affiliated authors
- maciel, carlos dias (~1)
- santos, moisés rocha dos (~1)
- santos, talysson manoel de oliveira (~1)
- tsukahara, victor hugo batista (~1)
Date published
- 2019 (~2)
Subjects
- aprendizado computacional (1)
- eletroencefalografia (1)
- engenharia elétrica (1)
- epilepsia (1)
- processamento digital de sinais (1)

Trabalho de evento-anais periodico
Graph model evolution during epileptic seizures: linear model approach (2019)
Santos, Talysson Manoel de Oliveira; Tsukahara, Victor Hugo Batista; Oliveira, Jasiara C. de; Cota, Vinicius Rosa; Maciel, Carlos Dias
Source: Communications in Computer and Information Science. Conference titles: Latin American Workshop on Computational Neuroscience - LAWCN. Unidade: EESC
Subjects: ELETROENCEFALOGRAFIA, EPILEPSIA, PROCESSAMENTO DIGITAL DE SINAIS, ENGENHARIA ELÉTRICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Talysson Manoel de Oliveira et al. Graph model evolution during epileptic seizures: linear model approach. Communications in Computer and Information Science. Cham, Switzerland: Springer. Disponível em: https://doi.org/10.1007/978-3-030-36636-0_12. Acesso em: 07 nov. 2025. , 2019
APA
Santos, T. M. de O., Tsukahara, V. H. B., Oliveira, J. C. de, Cota, V. R., & Maciel, C. D. (2019). Graph model evolution during epileptic seizures: linear model approach. Communications in Computer and Information Science. Cham, Switzerland: Springer. doi:10.1007/978-3-030-36636-0_12
NLM
Santos TM de O, Tsukahara VHB, Oliveira JC de, Cota VR, Maciel CD. Graph model evolution during epileptic seizures: linear model approach [Internet]. Communications in Computer and Information Science. 2019 ; 1068 20-29.[citado 2025 nov. 07 ] Available from: https://doi.org/10.1007/978-3-030-36636-0_12
Vancouver
Santos TM de O, Tsukahara VHB, Oliveira JC de, Cota VR, Maciel CD. Graph model evolution during epileptic seizures: linear model approach [Internet]. Communications in Computer and Information Science. 2019 ; 1068 20-29.[citado 2025 nov. 07 ] Available from: https://doi.org/10.1007/978-3-030-36636-0_12
Trabalho de evento-anais periodico
Motor learning and machine learning: predicting the amount of sessions to learn the tracing task (2019)
Souza, Eduardo Dorneles Ferreira de; Santos, Moises Rocha dos ; Silva, Lucas Cléopas Costa da; Oliveira, Alexandre César Muniz de; Almeida Neto, Areolino de; Ribeiro, Paulo Rogério de Almeida
Source: Communications in Computer and Information Science. Conference titles: Latin American Workshop on Computational Neuroscience - LAWCN. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, REDES NEURAIS, REABILITAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUZA, Eduardo Dorneles Ferreira de et al. Motor learning and machine learning: predicting the amount of sessions to learn the tracing task. Communications in Computer and Information Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-36636-0_2. Acesso em: 07 nov. 2025. , 2019
APA
Souza, E. D. F. de, Santos, M. R. dos, Silva, L. C. C. da, Oliveira, A. C. M. de, Almeida Neto, A. de, & Ribeiro, P. R. de A. (2019). Motor learning and machine learning: predicting the amount of sessions to learn the tracing task. Communications in Computer and Information Science. Cham: Springer. doi:10.1007/978-3-030-36636-0_2
NLM
Souza EDF de, Santos MR dos, Silva LCC da, Oliveira ACM de, Almeida Neto A de, Ribeiro PR de A. Motor learning and machine learning: predicting the amount of sessions to learn the tracing task [Internet]. Communications in Computer and Information Science. 2019 ; 1068 20-29.[citado 2025 nov. 07 ] Available from: https://doi.org/10.1007/978-3-030-36636-0_2
Vancouver
Souza EDF de, Santos MR dos, Silva LCC da, Oliveira ACM de, Almeida Neto A de, Ribeiro PR de A. Motor learning and machine learning: predicting the amount of sessions to learn the tracing task [Internet]. Communications in Computer and Information Science. 2019 ; 1068 20-29.[citado 2025 nov. 07 ] Available from: https://doi.org/10.1007/978-3-030-36636-0_2

Digital Library of Intellectual Production of Universidade de São Paulo 2012 - 2025