ReP USP - Resultado da busca

Filtros : "Wuttisittikulkij, Lunchakorn" Limpar

Filtros

Artigo de periodico
Enhanced routing algorithm based on reinforcement machine learning: a case of voIP service (2021)
Militani, Davi Ribeiro; Moraes, Hermes Pimenta de; Rosa, Renata Lopes; Zegarra Rodriguez, Demóstenes ; Arjona Ramírez, Miguel ; Wuttisittikulkij, Lunchakorn
Source: Sensors. Unidade: EP
Subjects: APRENDIZADO COMPUTACIONAL, INSTRUÇÃO PROGRAMADA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MILITANI, Davi Ribeiro et al. Enhanced routing algorithm based on reinforcement machine learning: a case of voIP service. Sensors, v. 21, n. 2, p. 504-536, 2021Tradução . . Disponível em: https://doi.org/10.3390/s21020504. Acesso em: 21 maio 2024.
APA
Militani, D. R., Moraes, H. P. de, Rosa, R. L., Zegarra Rodriguez, D., Arjona Ramírez, M., & Wuttisittikulkij, L. (2021). Enhanced routing algorithm based on reinforcement machine learning: a case of voIP service. Sensors, 21( 2), 504-536. doi:10.3390/s21020504
NLM
Militani DR, Moraes HP de, Rosa RL, Zegarra Rodriguez D, Arjona Ramírez M, Wuttisittikulkij L. Enhanced routing algorithm based on reinforcement machine learning: a case of voIP service [Internet]. Sensors. 2021 ;21( 2): 504-536.[citado 2024 maio 21 ] Available from: https://doi.org/10.3390/s21020504
Vancouver
Militani DR, Moraes HP de, Rosa RL, Zegarra Rodriguez D, Arjona Ramírez M, Wuttisittikulkij L. Enhanced routing algorithm based on reinforcement machine learning: a case of voIP service [Internet]. Sensors. 2021 ;21( 2): 504-536.[citado 2024 maio 21 ] Available from: https://doi.org/10.3390/s21020504
Artigo de periodico
Q-Meter: quality monitoring system for telecommunication services based on sentiment analysis using deep learning (2021)
Vieira, Samuel Terra; Rosa, Renata Lopes; Zegarra Rodriguez, Demóstenes ; Arjona Ramírez, Miguel ; Saadi, Muhammad; Wuttisittikulkij, Lunchakorn
Source: Sensors. Unidade: EP
Subjects: TELECOMUNICAÇÕES, REDES SOCIAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
VIEIRA, Samuel Terra et al. Q-Meter: quality monitoring system for telecommunication services based on sentiment analysis using deep learning. Sensors, v. 21, n. 5, p. 1-18, 2021Tradução . . Disponível em: https://doi.org/10.3390/s21051880. Acesso em: 21 maio 2024.
APA
Vieira, S. T., Rosa, R. L., Zegarra Rodriguez, D., Arjona Ramírez, M., Saadi, M., & Wuttisittikulkij, L. (2021). Q-Meter: quality monitoring system for telecommunication services based on sentiment analysis using deep learning. Sensors, 21( 5), 1-18. doi:10.3390/s21051880
NLM
Vieira ST, Rosa RL, Zegarra Rodriguez D, Arjona Ramírez M, Saadi M, Wuttisittikulkij L. Q-Meter: quality monitoring system for telecommunication services based on sentiment analysis using deep learning [Internet]. Sensors. 2021 ;21( 5): 1-18.[citado 2024 maio 21 ] Available from: https://doi.org/10.3390/s21051880
Vancouver
Vieira ST, Rosa RL, Zegarra Rodriguez D, Arjona Ramírez M, Saadi M, Wuttisittikulkij L. Q-Meter: quality monitoring system for telecommunication services based on sentiment analysis using deep learning [Internet]. Sensors. 2021 ;21( 5): 1-18.[citado 2024 maio 21 ] Available from: https://doi.org/10.3390/s21051880

Digital Library of Intellectual Production of Universidade de São Paulo 2012 - 2024