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Trabalho de evento
Improving semantic role labeling using high-level classification in complex networks (2017)
Carneiro, Murilo G; Rosa, João Luís Garcia ; Qiusheng, Zheng; Xiaoming, Liu; Liang, Zhao
Fonte: Proceedings. Nome do evento: International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery - ICNC-FSKD. Unidades: ICMC, FFCLRP
Assuntos: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CARNEIRO, Murilo G et al. Improving semantic role labeling using high-level classification in complex networks. 2017, Anais.. Los Alamitos: IEEE, 2017. Disponível em: https://doi.org/10.1109/FSKD.2017.8393113. Acesso em: 22 jun. 2024.
APA
Carneiro, M. G., Rosa, J. L. G., Qiusheng, Z., Xiaoming, L., & Liang, Z. (2017). Improving semantic role labeling using high-level classification in complex networks. In Proceedings. Los Alamitos: IEEE. doi:10.1109/FSKD.2017.8393113
NLM
Carneiro MG, Rosa JLG, Qiusheng Z, Xiaoming L, Liang Z. Improving semantic role labeling using high-level classification in complex networks [Internet]. Proceedings. 2017 ;[citado 2024 jun. 22 ] Available from: https://doi.org/10.1109/FSKD.2017.8393113
Vancouver
Carneiro MG, Rosa JLG, Qiusheng Z, Xiaoming L, Liang Z. Improving semantic role labeling using high-level classification in complex networks [Internet]. Proceedings. 2017 ;[citado 2024 jun. 22 ] Available from: https://doi.org/10.1109/FSKD.2017.8393113
Trabalho de evento
Stochastic and deterministic stationarity analysis of EEG data (2017)
Cestari, Daniel Moreira; Rosa, João Luís Garcia
Fonte: Proceedings. Nome do evento: International Joint Conference on Neural Networks - IJCNN. Unidade: ICMC
Assuntos: ANÁLISE DE SÉRIES TEMPORAIS, PROCESSAMENTO DE SINAIS BIOMÉDICOS, TECNOLOGIAS DA SAÚDE, ELETROENCEFALOGRAFIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CESTARI, Daniel Moreira e ROSA, João Luís Garcia. Stochastic and deterministic stationarity analysis of EEG data. 2017, Anais.. Piscataway: IEEE, 2017. Disponível em: https://doi.org/10.1109/IJCNN.2017.7965837. Acesso em: 22 jun. 2024.
APA
Cestari, D. M., & Rosa, J. L. G. (2017). Stochastic and deterministic stationarity analysis of EEG data. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN.2017.7965837
NLM
Cestari DM, Rosa JLG. Stochastic and deterministic stationarity analysis of EEG data [Internet]. Proceedings. 2017 ;[citado 2024 jun. 22 ] Available from: https://doi.org/10.1109/IJCNN.2017.7965837
Vancouver
Cestari DM, Rosa JLG. Stochastic and deterministic stationarity analysis of EEG data [Internet]. Proceedings. 2017 ;[citado 2024 jun. 22 ] Available from: https://doi.org/10.1109/IJCNN.2017.7965837
Artigo de periodico
How an epileptic EEG segment, used as reference, can influence a cross-correlation classifier? (2017)
Oliva, Jefferson Tales; Rosa, João Luís Garcia
Fonte: Applied Intelligence. Unidade: ICMC
Assuntos: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE SINAIS, MINERAÇÃO DE DADOS, ELETROENCEFALOGRAFIA, EPILEPSIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVA, Jefferson Tales e ROSA, João Luís Garcia. How an epileptic EEG segment, used as reference, can influence a cross-correlation classifier?. Applied Intelligence, v. 47, n. 1, p. 178-196, 2017Tradução . . Disponível em: https://doi.org/10.1007/s10489-016-0891-y. Acesso em: 22 jun. 2024.
APA
Oliva, J. T., & Rosa, J. L. G. (2017). How an epileptic EEG segment, used as reference, can influence a cross-correlation classifier? Applied Intelligence, 47( 1), 178-196. doi:10.1007/s10489-016-0891-y
NLM
Oliva JT, Rosa JLG. How an epileptic EEG segment, used as reference, can influence a cross-correlation classifier? [Internet]. Applied Intelligence. 2017 ; 47( 1): 178-196.[citado 2024 jun. 22 ] Available from: https://doi.org/10.1007/s10489-016-0891-y
Vancouver
Oliva JT, Rosa JLG. How an epileptic EEG segment, used as reference, can influence a cross-correlation classifier? [Internet]. Applied Intelligence. 2017 ; 47( 1): 178-196.[citado 2024 jun. 22 ] Available from: https://doi.org/10.1007/s10489-016-0891-y
Trabalho de evento
The use of one-class classifiers for differentiating healthy from epileptic EEG segments (2017)
Oliva, Jefferson Tales; Rosa, João Luís Garcia
Fonte: Proceedings. Nome do evento: International Joint Conference on Neural Networks - IJCNN. Unidade: ICMC
Assuntos: MINERAÇÃO DE DADOS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, PROCESSAMENTO DE SINAIS BIOMÉDICOS, ELETROENCEFALOGRAFIA, EPILEPSIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVA, Jefferson Tales e ROSA, João Luís Garcia. The use of one-class classifiers for differentiating healthy from epileptic EEG segments. 2017, Anais.. Piscataway: IEEE, 2017. Disponível em: https://doi.org/10.1109/IJCNN.2017.7966222. Acesso em: 22 jun. 2024.
APA
Oliva, J. T., & Rosa, J. L. G. (2017). The use of one-class classifiers for differentiating healthy from epileptic EEG segments. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN.2017.7966222
NLM
Oliva JT, Rosa JLG. The use of one-class classifiers for differentiating healthy from epileptic EEG segments [Internet]. Proceedings. 2017 ;[citado 2024 jun. 22 ] Available from: https://doi.org/10.1109/IJCNN.2017.7966222
Vancouver
Oliva JT, Rosa JLG. The use of one-class classifiers for differentiating healthy from epileptic EEG segments [Internet]. Proceedings. 2017 ;[citado 2024 jun. 22 ] Available from: https://doi.org/10.1109/IJCNN.2017.7966222
Trabalho de evento
Restricted exhaustive search for frequency band selection in motor imagery classification (2017)
Bustios, Paul; Rosa, João Luís Garcia
Fonte: Proceedings. Nome do evento: International Joint Conference on Neural Networks - IJCNN. Unidade: ICMC
Assuntos: RECONHECIMENTO DE PADRÕES, PROCESSAMENTO DE SINAIS BIOMÉDICOS, TECNOLOGIAS DA SAÚDE, ELETROENCEFALOGRAFIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BUSTIOS, Paul e ROSA, João Luís Garcia. Restricted exhaustive search for frequency band selection in motor imagery classification. 2017, Anais.. Piscataway: IEEE, 2017. Disponível em: https://doi.org/10.1109/IJCNN.2017.7966388. Acesso em: 22 jun. 2024.
APA
Bustios, P., & Rosa, J. L. G. (2017). Restricted exhaustive search for frequency band selection in motor imagery classification. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN.2017.7966388
NLM
Bustios P, Rosa JLG. Restricted exhaustive search for frequency band selection in motor imagery classification [Internet]. Proceedings. 2017 ;[citado 2024 jun. 22 ] Available from: https://doi.org/10.1109/IJCNN.2017.7966388
Vancouver
Bustios P, Rosa JLG. Restricted exhaustive search for frequency band selection in motor imagery classification [Internet]. Proceedings. 2017 ;[citado 2024 jun. 22 ] Available from: https://doi.org/10.1109/IJCNN.2017.7966388
Trabalho de evento-anais periodico
Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques (2017)
Oliva, Jefferson Tales; Rosa, João Luís Garcia
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Banff International Research Station for Mathematical Innovation and Discovery Workshop - BIRS. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, RECONHECIMENTO DE PADRÕES, ELETROENCEFALOGRAFIA, EPILEPSIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVA, Jefferson Tales e ROSA, João Luís Garcia. Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-69775-8_7. Acesso em: 22 jun. 2024. , 2017
APA
Oliva, J. T., & Rosa, J. L. G. (2017). Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-319-69775-8_7
NLM
Oliva JT, Rosa JLG. Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques [Internet]. Lecture Notes in Artificial Intelligence. 2017 ; 10344 134-145.[citado 2024 jun. 22 ] Available from: https://doi.org/10.1007/978-3-319-69775-8_7
Vancouver
Oliva JT, Rosa JLG. Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques [Internet]. Lecture Notes in Artificial Intelligence. 2017 ; 10344 134-145.[citado 2024 jun. 22 ] Available from: https://doi.org/10.1007/978-3-319-69775-8_7

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