ReP USP - Resultado da busca

Artigo de periodico
Neural network training fingerprint: visual analytics of the training process in classification neural networks (2022)
Ferreira, Martha Dais ; Cantareira, Gabriel Dias ; Mello, Rodrigo Fernandes de ; Paulovich, Fernando Vieira
Source: Journal of Visualization. Unidade: ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, VISUALIZAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FERREIRA, Martha Dais et al. Neural network training fingerprint: visual analytics of the training process in classification neural networks. Journal of Visualization, v. 25, n. 3, p. 593-612, 2022Tradução . . Disponível em: https://doi.org/10.1007/s12650-021-00809-4. Acesso em: 28 jul. 2024.
APA
Ferreira, M. D., Cantareira, G. D., Mello, R. F. de, & Paulovich, F. V. (2022). Neural network training fingerprint: visual analytics of the training process in classification neural networks. Journal of Visualization, 25( 3), 593-612. doi:10.1007/s12650-021-00809-4
NLM
Ferreira MD, Cantareira GD, Mello RF de, Paulovich FV. Neural network training fingerprint: visual analytics of the training process in classification neural networks [Internet]. Journal of Visualization. 2022 ; 25( 3): 593-612.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1007/s12650-021-00809-4
Vancouver
Ferreira MD, Cantareira GD, Mello RF de, Paulovich FV. Neural network training fingerprint: visual analytics of the training process in classification neural networks [Internet]. Journal of Visualization. 2022 ; 25( 3): 593-612.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1007/s12650-021-00809-4
Artigo de periodico
Autonomous CNN (AutoCNN): a data-driven approach to network architecture determination (2022)
Aradhya, Abhay M. S ; Ashfahani, Andri; Angelina, Fienny; Pratama, Mahardhika ; Mello, Rodrigo Fernandes de ; Sundaram, Suresh
Source: Information Sciences. Unidade: ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, COMPUTAÇÃO EVOLUTIVA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ARADHYA, Abhay M. S et al. Autonomous CNN (AutoCNN): a data-driven approach to network architecture determination. Information Sciences, v. 607, p. 638-653, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2022.05.100. Acesso em: 28 jul. 2024.
APA
Aradhya, A. M. S., Ashfahani, A., Angelina, F., Pratama, M., Mello, R. F. de, & Sundaram, S. (2022). Autonomous CNN (AutoCNN): a data-driven approach to network architecture determination. Information Sciences, 607, 638-653. doi:10.1016/j.ins.2022.05.100
NLM
Aradhya AMS, Ashfahani A, Angelina F, Pratama M, Mello RF de, Sundaram S. Autonomous CNN (AutoCNN): a data-driven approach to network architecture determination [Internet]. Information Sciences. 2022 ; 607 638-653.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1016/j.ins.2022.05.100
Vancouver
Aradhya AMS, Ashfahani A, Angelina F, Pratama M, Mello RF de, Sundaram S. Autonomous CNN (AutoCNN): a data-driven approach to network architecture determination [Internet]. Information Sciences. 2022 ; 607 638-653.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1016/j.ins.2022.05.100
Artigo de periodico
Llaima volcano dataset: in-depth comparison of deep artificial neural network architectures on seismic events classification (2020)
Canário, João Paulo ; Mello, Rodrigo Fernandes de ; Curilem, Millaray ; Huenupan, Fernando ; Rios, Ricardo Araújo
Source: Data in Brief. Unidade: ICMC
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, REDES NEURAIS, VULCÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CANÁRIO, João Paulo et al. Llaima volcano dataset: in-depth comparison of deep artificial neural network architectures on seismic events classification. Data in Brief, v. 30, p. 1-6, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.dib.2020.105627. Acesso em: 28 jul. 2024.
APA
Canário, J. P., Mello, R. F. de, Curilem, M., Huenupan, F., & Rios, R. A. (2020). Llaima volcano dataset: in-depth comparison of deep artificial neural network architectures on seismic events classification. Data in Brief, 30, 1-6. doi:10.1016/j.dib.2020.105627
NLM
Canário JP, Mello RF de, Curilem M, Huenupan F, Rios RA. Llaima volcano dataset: in-depth comparison of deep artificial neural network architectures on seismic events classification [Internet]. Data in Brief. 2020 ; 30 1-6.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1016/j.dib.2020.105627
Vancouver
Canário JP, Mello RF de, Curilem M, Huenupan F, Rios RA. Llaima volcano dataset: in-depth comparison of deep artificial neural network architectures on seismic events classification [Internet]. Data in Brief. 2020 ; 30 1-6.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1016/j.dib.2020.105627
Trabalho de evento-resumo
Random projections and α-shape to support the kernel design (2020)
Cestari, Daniel Moreira ; Mello, Rodrigo Fernandes de
Source: Proceedings. Conference titles: AAAI Conference on Artificial Intelligence - AAAI. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, RECONHECIMENTO DE PADRÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CESTARI, Daniel Moreira e MELLO, Rodrigo Fernandes de. Random projections and α-shape to support the kernel design. 2020, Anais.. Palo Alto: AAAI Press, 2020. Disponível em: https://doi.org/10.1609/aaai.v34i10.7211. Acesso em: 28 jul. 2024.
APA
Cestari, D. M., & Mello, R. F. de. (2020). Random projections and α-shape to support the kernel design. In Proceedings. Palo Alto: AAAI Press. doi:10.1609/aaai.v34i10.7211
NLM
Cestari DM, Mello RF de. Random projections and α-shape to support the kernel design [Internet]. Proceedings. 2020 ;[citado 2024 jul. 28 ] Available from: https://doi.org/10.1609/aaai.v34i10.7211
Vancouver
Cestari DM, Mello RF de. Random projections and α-shape to support the kernel design [Internet]. Proceedings. 2020 ;[citado 2024 jul. 28 ] Available from: https://doi.org/10.1609/aaai.v34i10.7211
Artigo de periodico
In-depth comparison of deep artificial neural network architectures on seismic events classification (2020)
Canário, João Paulo ; Mello, Rodrigo Fernandes de ; Curilem, Millaray ; Huenupan, Fernando ; Rios, Ricardo Araújo
Source: Journal of Volcanology and Geothermal Research. Unidade: ICMC
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, REDES NEURAIS, VULCÕES, ANÁLISE DE ONDALETAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CANÁRIO, João Paulo et al. In-depth comparison of deep artificial neural network architectures on seismic events classification. Journal of Volcanology and Geothermal Research, v. 401, p. Se 2020, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.jvolgeores.2020.106881. Acesso em: 28 jul. 2024.
APA
Canário, J. P., Mello, R. F. de, Curilem, M., Huenupan, F., & Rios, R. A. (2020). In-depth comparison of deep artificial neural network architectures on seismic events classification. Journal of Volcanology and Geothermal Research, 401, Se 2020. doi:10.1016/j.jvolgeores.2020.106881
NLM
Canário JP, Mello RF de, Curilem M, Huenupan F, Rios RA. In-depth comparison of deep artificial neural network architectures on seismic events classification [Internet]. Journal of Volcanology and Geothermal Research. 2020 ; 401 Se 2020.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1016/j.jvolgeores.2020.106881
Vancouver
Canário JP, Mello RF de, Curilem M, Huenupan F, Rios RA. In-depth comparison of deep artificial neural network architectures on seismic events classification [Internet]. Journal of Volcanology and Geothermal Research. 2020 ; 401 Se 2020.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1016/j.jvolgeores.2020.106881
Artigo de periodico
Theoretical learning guarantees applied to acoustic modeling (2019)
Shulby, Christopher D; Ferreira, Martha D; Mello, Rodrigo Fernandes de; Aluísio, Sandra Maria
Source: Journal of the Brazilian Computer Society. Unidade: ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE VOZ
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SHULBY, Christopher D et al. Theoretical learning guarantees applied to acoustic modeling. Journal of the Brazilian Computer Society, v. 25, p. 1-12, 2019Tradução . . Disponível em: https://doi.org/10.1186/s13173-018-0081-3. Acesso em: 28 jul. 2024.
APA
Shulby, C. D., Ferreira, M. D., Mello, R. F. de, & Aluísio, S. M. (2019). Theoretical learning guarantees applied to acoustic modeling. Journal of the Brazilian Computer Society, 25, 1-12. doi:10.1186/s13173-018-0081-3
NLM
Shulby CD, Ferreira MD, Mello RF de, Aluísio SM. Theoretical learning guarantees applied to acoustic modeling [Internet]. Journal of the Brazilian Computer Society. 2019 ; 25 1-12.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1186/s13173-018-0081-3
Vancouver
Shulby CD, Ferreira MD, Mello RF de, Aluísio SM. Theoretical learning guarantees applied to acoustic modeling [Internet]. Journal of the Brazilian Computer Society. 2019 ; 25 1-12.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1186/s13173-018-0081-3
Artigo de periodico
Designing architectures of convolutional neural networks to solve practical problems (2018)
Ferreira, Martha Dais; Corrêa, Débora Cristina; Nonato, Luis Gustavo ; Mello, Rodrigo Fernandes de
Source: Expert Systems with Applications. Unidade: ICMC
Subjects: REDES NEURAIS, SISTEMAS DINÂMICOS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE OBJETOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FERREIRA, Martha Dais et al. Designing architectures of convolutional neural networks to solve practical problems. Expert Systems with Applications, v. 94, p. 205-217, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2017.10.052. Acesso em: 28 jul. 2024.
APA
Ferreira, M. D., Corrêa, D. C., Nonato, L. G., & Mello, R. F. de. (2018). Designing architectures of convolutional neural networks to solve practical problems. Expert Systems with Applications, 94, 205-217. doi:10.1016/j.eswa.2017.10.052
NLM
Ferreira MD, Corrêa DC, Nonato LG, Mello RF de. Designing architectures of convolutional neural networks to solve practical problems [Internet]. Expert Systems with Applications. 2018 ; 94 205-217.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1016/j.eswa.2017.10.052
Vancouver
Ferreira MD, Corrêa DC, Nonato LG, Mello RF de. Designing architectures of convolutional neural networks to solve practical problems [Internet]. Expert Systems with Applications. 2018 ; 94 205-217.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1016/j.eswa.2017.10.052
Trabalho de evento
Acoustic modeling using a shallow CNN-HTSVM architecture (2017)
Shulby, Christopher Dane; Ferreira, Martha Dais; Mello, Rodrigo Fernandes de; Aluísio, Sandra Maria
Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE VOZ
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SHULBY, Christopher Dane et al. Acoustic modeling using a shallow CNN-HTSVM architecture. 2017, Anais.. Piscataway: IEEE, 2017. Disponível em: https://doi.org/10.1109/BRACIS.2017.62. Acesso em: 28 jul. 2024.
APA
Shulby, C. D., Ferreira, M. D., Mello, R. F. de, & Aluísio, S. M. (2017). Acoustic modeling using a shallow CNN-HTSVM architecture. In Proceedings. Piscataway: IEEE. doi:10.1109/BRACIS.2017.62
NLM
Shulby CD, Ferreira MD, Mello RF de, Aluísio SM. Acoustic modeling using a shallow CNN-HTSVM architecture [Internet]. Proceedings. 2017 ;[citado 2024 jul. 28 ] Available from: https://doi.org/10.1109/BRACIS.2017.62
Vancouver
Shulby CD, Ferreira MD, Mello RF de, Aluísio SM. Acoustic modeling using a shallow CNN-HTSVM architecture [Internet]. Proceedings. 2017 ;[citado 2024 jul. 28 ] Available from: https://doi.org/10.1109/BRACIS.2017.62
Trabalho de evento
Data clustering using topological features (2014)
Pereira, Cássio M. M; Mello, Rodrigo Fernandes de
Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Subjects: REDES NEURAIS, PROGRAMAÇÃO CONCORRENTE, SISTEMAS DINÂMICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PEREIRA, Cássio M. M e MELLO, Rodrigo Fernandes de. Data clustering using topological features. 2014, Anais.. Los Alamitos: Conference Publishing Services, 2014. Disponível em: https://doi.org/10.1109/BRACIS.2014.71. Acesso em: 28 jul. 2024.
APA
Pereira, C. M. M., & Mello, R. F. de. (2014). Data clustering using topological features. In Proceedings. Los Alamitos: Conference Publishing Services. doi:10.1109/BRACIS.2014.71
NLM
Pereira CMM, Mello RF de. Data clustering using topological features [Internet]. Proceedings. 2014 ;[citado 2024 jul. 28 ] Available from: https://doi.org/10.1109/BRACIS.2014.71
Vancouver
Pereira CMM, Mello RF de. Data clustering using topological features [Internet]. Proceedings. 2014 ;[citado 2024 jul. 28 ] Available from: https://doi.org/10.1109/BRACIS.2014.71
Artigo de periodico
Image indexing and retrieval using an ART-2A neural network architecture (2008)
Mello, Rodrigo Fernandes de; Bueno, Josiane Maria; Senger, Luciano José; Yang, Laurence T
Source: International Journal of Imaging Systems and Technology. Unidade: ICMC
Subjects: RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE IMAGEM, REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MELLO, Rodrigo Fernandes de et al. Image indexing and retrieval using an ART-2A neural network architecture. International Journal of Imaging Systems and Technology, v. 18, n. 2-3, p. 202-208, 2008Tradução . . Disponível em: https://doi.org/10.1002/ima.20149. Acesso em: 28 jul. 2024.
APA
Mello, R. F. de, Bueno, J. M., Senger, L. J., & Yang, L. T. (2008). Image indexing and retrieval using an ART-2A neural network architecture. International Journal of Imaging Systems and Technology, 18( 2-3), 202-208. doi:10.1002/ima.20149
NLM
Mello RF de, Bueno JM, Senger LJ, Yang LT. Image indexing and retrieval using an ART-2A neural network architecture [Internet]. International Journal of Imaging Systems and Technology. 2008 ; 18( 2-3): 202-208.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1002/ima.20149
Vancouver
Mello RF de, Bueno JM, Senger LJ, Yang LT. Image indexing and retrieval using an ART-2A neural network architecture [Internet]. International Journal of Imaging Systems and Technology. 2008 ; 18( 2-3): 202-208.[citado 2024 jul. 28 ] Available from: https://doi.org/10.1002/ima.20149
Trabalho de evento
Escalonamento de processos utilizando técnicas de ACO (2006)
Nery, Bruno Rodrigues; Mello, Rodrigo Fernandes de; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Anais. Conference titles: Congresso da Sociedade Brasileira de Computação - CSBC. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NERY, Bruno Rodrigues e MELLO, Rodrigo Fernandes de e CARVALHO, André Carlos Ponce de Leon Ferreira de. Escalonamento de processos utilizando técnicas de ACO. 2006, Anais.. Porto Alegre, RS: SBC, 2006. . Acesso em: 28 jul. 2024.
APA
Nery, B. R., Mello, R. F. de, & Carvalho, A. C. P. de L. F. de. (2006). Escalonamento de processos utilizando técnicas de ACO. In Anais. Porto Alegre, RS: SBC.
NLM
Nery BR, Mello RF de, Carvalho ACP de LF de. Escalonamento de processos utilizando técnicas de ACO. Anais. 2006 ;[citado 2024 jul. 28 ]
Vancouver
Nery BR, Mello RF de, Carvalho ACP de LF de. Escalonamento de processos utilizando técnicas de ACO. Anais. 2006 ;[citado 2024 jul. 28 ]

USP Schools

ReP

Filtros

Authors

Date published

Subjects

Source title

Funding Agencies

Indexado em

Non normalized affiliation

Countries of institutions of collaboration