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Artigo de periodico
Combining clustering and active learning for the detection and learning of new image classes (2019)
Coletta, Luiz Fernando Sommaggio ; Ponti, Moacir Antonelli ; Hruschka, Eduardo Raul ; Acharya, Ayan; Ghosh, Joydeep
Fonte: Neurocomputing. Unidades: ICMC, EP
Assuntos: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COLETTA, Luiz Fernando Sommaggio et al. Combining clustering and active learning for the detection and learning of new image classes. Neurocomputing, v. 358, p. Se 2019, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2019.04.070. Acesso em: 11 nov. 2025.
APA
Coletta, L. F. S., Ponti, M. A., Hruschka, E. R., Acharya, A., & Ghosh, J. (2019). Combining clustering and active learning for the detection and learning of new image classes. Neurocomputing, 358, Se 2019. doi:10.1016/j.neucom.2019.04.070
NLM
Coletta LFS, Ponti MA, Hruschka ER, Acharya A, Ghosh J. Combining clustering and active learning for the detection and learning of new image classes [Internet]. Neurocomputing. 2019 ; 358 Se 2019.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2019.04.070
Vancouver
Coletta LFS, Ponti MA, Hruschka ER, Acharya A, Ghosh J. Combining clustering and active learning for the detection and learning of new image classes [Internet]. Neurocomputing. 2019 ; 358 Se 2019.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2019.04.070
Artigo de periodico
Individual and collective properties of computationally efficient motoneuron models of types S and F with active dendrites (2013)
Elias, Leonardo Abdala; Kohn, André Fábio
Fonte: Neurocomputing. Unidade: EP
Assuntos: NEURÔNIOS, CONTROLE MOTOR, NEUROCIÊNCIAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ELIAS, Leonardo Abdala e KOHN, André Fábio. Individual and collective properties of computationally efficient motoneuron models of types S and F with active dendrites. Neurocomputing, v. 99, p. 521-533, 2013Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2012.06.038. Acesso em: 11 nov. 2025.
APA
Elias, L. A., & Kohn, A. F. (2013). Individual and collective properties of computationally efficient motoneuron models of types S and F with active dendrites. Neurocomputing, 99, 521-533. doi:10.1016/j.neucom.2012.06.038
NLM
Elias LA, Kohn AF. Individual and collective properties of computationally efficient motoneuron models of types S and F with active dendrites [Internet]. Neurocomputing. 2013 ; 99 521-533.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2012.06.038
Vancouver
Elias LA, Kohn AF. Individual and collective properties of computationally efficient motoneuron models of types S and F with active dendrites [Internet]. Neurocomputing. 2013 ; 99 521-533.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2012.06.038
Artigo de periodico
Shannon's entropy applied to the analysis of tonotopic reorganization in a computational model of classical conditioning (2002)
Pinho, Marilene de; Mazza, Marcelo; Piqueira, José Roberto Castilho ; Roque, Antônio Carlos
Fonte: Neurocomputing. Unidades: EP, FFCLRP
Assuntos: ENTROPIA, MATEMÁTICA APLICADA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PINHO, Marilene de et al. Shannon's entropy applied to the analysis of tonotopic reorganization in a computational model of classical conditioning. Neurocomputing, v. 44-46, p. 359-364, 2002Tradução . . Disponível em: https://doi.org/10.1016/s0925-2312(02)00382-x. Acesso em: 11 nov. 2025.
APA
Pinho, M. de, Mazza, M., Piqueira, J. R. C., & Roque, A. C. (2002). Shannon's entropy applied to the analysis of tonotopic reorganization in a computational model of classical conditioning. Neurocomputing, 44-46, 359-364. doi:10.1016/s0925-2312(02)00382-x
NLM
Pinho M de, Mazza M, Piqueira JRC, Roque AC. Shannon's entropy applied to the analysis of tonotopic reorganization in a computational model of classical conditioning [Internet]. Neurocomputing. 2002 ; 44-46 359-364.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/s0925-2312(02)00382-x
Vancouver
Pinho M de, Mazza M, Piqueira JRC, Roque AC. Shannon's entropy applied to the analysis of tonotopic reorganization in a computational model of classical conditioning [Internet]. Neurocomputing. 2002 ; 44-46 359-364.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/s0925-2312(02)00382-x
Artigo de periodico
Using information theory for the analysis of cortical reorganization in a realistic computational model of the somatosensory system (2002)
Mazza, Marcelo; Pinho, Marilene de; Piqueira, José Roberto Castilho ; Roque, Antônio Carlos
Fonte: Neurocomputing. Unidades: EP, FFCLRP
Assuntos: ENTROPIA, MATEMÁTICA APLICADA, RECEPTORES SENSORIAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MAZZA, Marcelo et al. Using information theory for the analysis of cortical reorganization in a realistic computational model of the somatosensory system. Neurocomputing, v. 44-46, p. 923-928, 2002Tradução . . Disponível em: https://doi.org/10.1016/s0925-2312(02)00492-7. Acesso em: 11 nov. 2025.
APA
Mazza, M., Pinho, M. de, Piqueira, J. R. C., & Roque, A. C. (2002). Using information theory for the analysis of cortical reorganization in a realistic computational model of the somatosensory system. Neurocomputing, 44-46, 923-928. doi:10.1016/s0925-2312(02)00492-7
NLM
Mazza M, Pinho M de, Piqueira JRC, Roque AC. Using information theory for the analysis of cortical reorganization in a realistic computational model of the somatosensory system [Internet]. Neurocomputing. 2002 ; 44-46 923-928.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/s0925-2312(02)00492-7
Vancouver
Mazza M, Pinho M de, Piqueira JRC, Roque AC. Using information theory for the analysis of cortical reorganization in a realistic computational model of the somatosensory system [Internet]. Neurocomputing. 2002 ; 44-46 923-928.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/s0925-2312(02)00492-7

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