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Trabalho de evento-anais periodico
Effective layer pruning through similarity metric perspective (2025)
Pons, Ian; Yamamoto, Bruno Lopes; Reali Costa, Anna Helena ; Correia, Artur Jordão Lima
Fonte: Lecture Notes in Computer Science. Nome do evento: International Conference on Pattern Recognition - ICPR 2024:Proceedings-Part V. Unidade: EP
Assuntos: APRENDIZAGEM PROFUNDA, REDES NEURAIS, ESPAÇOS MÉTRICOS
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ABNT
PONS, Ian et al. Effective layer pruning through similarity metric perspective. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-78169-8_8. Acesso em: 20 nov. 2025. , 2025
APA
Pons, I., Yamamoto, B. L., Reali Costa, A. H., & Correia, A. J. L. (2025). Effective layer pruning through similarity metric perspective. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-031-78169-8_28
NLM
Pons I, Yamamoto BL, Reali Costa AH, Correia AJL. Effective layer pruning through similarity metric perspective [Internet]. Lecture Notes in Computer Science. 2025 ; 15305 423-438.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-031-78169-8_8
Vancouver
Pons I, Yamamoto BL, Reali Costa AH, Correia AJL. Effective layer pruning through similarity metric perspective [Internet]. Lecture Notes in Computer Science. 2025 ; 15305 423-438.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-031-78169-8_8
Trabalho de evento-anais periodico
Bipartite graph coarsening for text classification using graph neural networks (2024)
Santos, Nícolas Roque dos ; Minatel, Diego ; Valejo, Alan Demetrius Baria ; Lopes, Alneu de Andrade
Fonte: Lecture Notes in Computer Science. Nome do evento: Iberoamerican Congress on Pattern Recognition - CIARP. Unidade: ICMC
Assuntos: MINERAÇÃO DE DADOS, REDES NEURAIS
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ABNT
SANTOS, Nícolas Roque dos et al. Bipartite graph coarsening for text classification using graph neural networks. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-49018-7_42. Acesso em: 20 nov. 2025. , 2024
APA
Santos, N. R. dos, Minatel, D., Valejo, A. D. B., & Lopes, A. de A. (2024). Bipartite graph coarsening for text classification using graph neural networks. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-031-49018-7_42
NLM
Santos NR dos, Minatel D, Valejo ADB, Lopes A de A. Bipartite graph coarsening for text classification using graph neural networks [Internet]. Lecture Notes in Computer Science. 2024 ; 14469 589-604.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-031-49018-7_42
Vancouver
Santos NR dos, Minatel D, Valejo ADB, Lopes A de A. Bipartite graph coarsening for text classification using graph neural networks [Internet]. Lecture Notes in Computer Science. 2024 ; 14469 589-604.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-031-49018-7_42
Trabalho de evento-anais periodico
Applying LSTM recurrent neural networks to predict revenue (2024)
Cardoso, Luis Eduardo Pelin ; Carvalho, Andre Carlos Ponce de Leon Ferreira de ; Quiles, Marcos Gonçalves
Fonte: Lecture Notes in Computer Science. Nome do evento: International Conference on Computational Science and its Applications - ICCSA. Unidade: ICMC
Assuntos: PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), REDES NEURAIS, PREVISÃO DE VENDAS
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ABNT
CARDOSO, Luis Eduardo Pelin e CARVALHO, Andre Carlos Ponce de Leon Ferreira de e QUILES, Marcos Gonçalves. Applying LSTM recurrent neural networks to predict revenue. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-64608-9_13. Acesso em: 20 nov. 2025. , 2024
APA
Cardoso, L. E. P., Carvalho, A. C. P. de L. F. de, & Quiles, M. G. (2024). Applying LSTM recurrent neural networks to predict revenue. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-031-64608-9_13
NLM
Cardoso LEP, Carvalho ACP de LF de, Quiles MG. Applying LSTM recurrent neural networks to predict revenue [Internet]. Lecture Notes in Computer Science. 2024 ; 14814 198-212.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-031-64608-9_13
Vancouver
Cardoso LEP, Carvalho ACP de LF de, Quiles MG. Applying LSTM recurrent neural networks to predict revenue [Internet]. Lecture Notes in Computer Science. 2024 ; 14814 198-212.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-031-64608-9_13
Trabalho de evento-anais periodico
Evaluate pseudo labeling and CNN for multi-variate time series classification in low-data regimes (2021)
Ienco, Dino ; Pereira-Santos, Davi; Carvalho, André Carlos Ponce de Leon Ferreira de
Fonte: Lecture Notes in Computer Science. Nome do evento: International Conference on Artificial Neural Networks - ICANN. Unidade: ICMC
Assuntos: ANÁLISE DE SÉRIES TEMPORAIS, REDES NEURAIS, APRENDIZADO COMPUTACIONAL
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ABNT
IENCO, Dino e PEREIRA-SANTOS, Davi e CARVALHO, André Carlos Ponce de Leon Ferreira de. Evaluate pseudo labeling and CNN for multi-variate time series classification in low-data regimes. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-86383-8_10. Acesso em: 20 nov. 2025. , 2021
APA
Ienco, D., Pereira-Santos, D., & Carvalho, A. C. P. de L. F. de. (2021). Evaluate pseudo labeling and CNN for multi-variate time series classification in low-data regimes. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-030-86383-8_10
NLM
Ienco D, Pereira-Santos D, Carvalho ACP de LF de. Evaluate pseudo labeling and CNN for multi-variate time series classification in low-data regimes [Internet]. Lecture Notes in Computer Science. 2021 ; 12895 126-137.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-030-86383-8_10
Vancouver
Ienco D, Pereira-Santos D, Carvalho ACP de LF de. Evaluate pseudo labeling and CNN for multi-variate time series classification in low-data regimes [Internet]. Lecture Notes in Computer Science. 2021 ; 12895 126-137.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-030-86383-8_10
Trabalho de evento-anais periodico
A serious game to build a database for ErrP signal recognition (2019)
Pinto, Adam Henrique Moreira ; Nardari, Guilherme Vicentim; Mijan, Marco Aurélio Martins; Morya, Edgard; Romero, Roseli Aparecida Francelin
Fonte: Lecture Notes in Computer Science. Nome do evento: International Work-Conference on Artificial Neural Networks - IWANN. Unidades: ICMC, EESC
Assuntos: INTERAÇÃO USUÁRIO-COMPUTADOR, SINAIS BIOMÉDICOS, ROBÓTICA, REDES NEURAIS
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ABNT
PINTO, Adam Henrique Moreira et al. A serious game to build a database for ErrP signal recognition. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-20518-8_16. Acesso em: 20 nov. 2025. , 2019
APA
Pinto, A. H. M., Nardari, G. V., Mijan, M. A. M., Morya, E., & Romero, R. A. F. (2019). A serious game to build a database for ErrP signal recognition. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-030-20518-8_16
NLM
Pinto AHM, Nardari GV, Mijan MAM, Morya E, Romero RAF. A serious game to build a database for ErrP signal recognition [Internet]. Lecture Notes in Computer Science. 2019 ; 11507 186-197.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-030-20518-8_16
Vancouver
Pinto AHM, Nardari GV, Mijan MAM, Morya E, Romero RAF. A serious game to build a database for ErrP signal recognition [Internet]. Lecture Notes in Computer Science. 2019 ; 11507 186-197.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-030-20518-8_16
Trabalho de evento-anais periodico
Deep convolutional neural networks and noisy images (2018)
Nazaré, Tiago Santana de ; Costa, Gabriel B. Paranhos da; Contato, Welinton A; Ponti, Moacir Antonelli
Fonte: Lecture Notes in Computer Science. Nome do evento: Iberoamerican Congress on Pattern Recognition - CIARP : Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, REDES NEURAIS
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ABNT
NAZARÉ, Tiago Santana de et al. Deep convolutional neural networks and noisy images. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-75193-1_50. Acesso em: 20 nov. 2025. , 2018
APA
Nazaré, T. S. de, Costa, G. B. P. da, Contato, W. A., & Ponti, M. A. (2018). Deep convolutional neural networks and noisy images. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-319-75193-1_50
NLM
Nazaré TS de, Costa GBP da, Contato WA, Ponti MA. Deep convolutional neural networks and noisy images [Internet]. Lecture Notes in Computer Science. 2018 ; 10657 416-424.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-319-75193-1_50
Vancouver
Nazaré TS de, Costa GBP da, Contato WA, Ponti MA. Deep convolutional neural networks and noisy images [Internet]. Lecture Notes in Computer Science. 2018 ; 10657 416-424.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-319-75193-1_50
Trabalho de evento-resumo periodico
A fault-tolerant indoor localization system with recurrent neural networks (2017)
Carvalho, Eduardo Costa de; Ferreira, Bruno Victor de Mesquita; Rocha Filho, Geraldo Pereira ; Ueyama, Jó ; Pessin, Gustavo
Fonte: Lecture Notes in Computer Science. Nome do evento: International Conference on Artificial Neural Networks - ICANN. Unidade: ICMC
Assuntos: COMPUTAÇÃO MÓVEL, FALHAS COMPUTACIONAIS, APRENDIZADO COMPUTACIONAL, REDES NEURAIS, PROCESSAMENTO DE SINAIS, WIRELESS
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ABNT
CARVALHO, Eduardo Costa de et al. A fault-tolerant indoor localization system with recurrent neural networks. Lecture Notes in Computer Science. Cham: Springer Nature Switzerland AG. Disponível em: https://doi.org/10.1007/978-3-319-68612-7. Acesso em: 20 nov. 2025. , 2017
APA
Carvalho, E. C. de, Ferreira, B. V. de M., Rocha Filho, G. P., Ueyama, J., & Pessin, G. (2017). A fault-tolerant indoor localization system with recurrent neural networks. Lecture Notes in Computer Science. Cham: Springer Nature Switzerland AG. doi:10.1007/978-3-319-68612-7
NLM
Carvalho EC de, Ferreira BV de M, Rocha Filho GP, Ueyama J, Pessin G. A fault-tolerant indoor localization system with recurrent neural networks [Internet]. Lecture Notes in Computer Science. 2017 ; 10614 761-762.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-319-68612-7
Vancouver
Carvalho EC de, Ferreira BV de M, Rocha Filho GP, Ueyama J, Pessin G. A fault-tolerant indoor localization system with recurrent neural networks [Internet]. Lecture Notes in Computer Science. 2017 ; 10614 761-762.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-319-68612-7
Trabalho de evento-anais periodico
Neural network based approach for automotive brake light parameter estimation (2012)
Ortega, Antonio Vanderlei; Silva, Ivan Nunes da
Fonte: Lecture Notes in Computer Science. Nome do evento: International Conference on Neural Information Processing - ICONIP. Unidade: EESC
Assuntos: LUZ, FREIOS, SISTEMAS VEICULARES, REDES NEURAIS
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ABNT
ORTEGA, Antonio Vanderlei e SILVA, Ivan Nunes da. Neural network based approach for automotive brake light parameter estimation. Lecture Notes in Computer Science. Heidelberg: Escola de Engenharia de São Carlos, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/978-3-642-34478-7_74. Acesso em: 20 nov. 2025. , 2012
APA
Ortega, A. V., & Silva, I. N. da. (2012). Neural network based approach for automotive brake light parameter estimation. Lecture Notes in Computer Science. Heidelberg: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.1007/978-3-642-34478-7_74
NLM
Ortega AV, Silva IN da. Neural network based approach for automotive brake light parameter estimation [Internet]. Lecture Notes in Computer Science. 2012 ; 7666 611-618.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-642-34478-7_74
Vancouver
Ortega AV, Silva IN da. Neural network based approach for automotive brake light parameter estimation [Internet]. Lecture Notes in Computer Science. 2012 ; 7666 611-618.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-642-34478-7_74
Trabalho de evento-anais periodico
Fault identification in doubly fed induction generator using FFT and neural networks (2012)
Santana, Marcelo Patrício de; Monteiro, José Roberto Boffino de Almeida ; Paula, Geyverson Teixeira de; Almeida, Thales Eugenio Portes de; Romero, Gustavo Bueno; Faracco, Júlio César
Fonte: Lecture Notes in Computer Science. Nome do evento: International Conference on Intelligent Data Engineering and Automated Learning. Unidade: EESC
Assuntos: REDES NEURAIS, TRANSFORMADA DE FOURIER
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ABNT
SANTANA, Marcelo Patrício de et al. Fault identification in doubly fed induction generator using FFT and neural networks. Lecture Notes in Computer Science. Heidelberg: Escola de Engenharia de São Carlos, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/978-3-642-32639-4_83. Acesso em: 20 nov. 2025. , 2012
APA
Santana, M. P. de, Monteiro, J. R. B. de A., Paula, G. T. de, Almeida, T. E. P. de, Romero, G. B., & Faracco, J. C. (2012). Fault identification in doubly fed induction generator using FFT and neural networks. Lecture Notes in Computer Science. Heidelberg: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.1007/978-3-642-32639-4_83
NLM
Santana MP de, Monteiro JRB de A, Paula GT de, Almeida TEP de, Romero GB, Faracco JC. Fault identification in doubly fed induction generator using FFT and neural networks [Internet]. Lecture Notes in Computer Science. 2012 ; 7435 699-706.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-642-32639-4_83
Vancouver
Santana MP de, Monteiro JRB de A, Paula GT de, Almeida TEP de, Romero GB, Faracco JC. Fault identification in doubly fed induction generator using FFT and neural networks [Internet]. Lecture Notes in Computer Science. 2012 ; 7435 699-706.[citado 2025 nov. 20 ] Available from: https://doi.org/10.1007/978-3-642-32639-4_83
Trabalho de evento-anais periodico
Language and cognition integration through modeling field theory: category formation for symbol grounding (2006)
Tikhanoff, Vadim; Fontanari, José Fernando ; Cangelosi, Angelo; Perlovsky, Leonid I.
Fonte: Lecture Notes in Computer Science. Nome do evento: International Conference Artificial Neural Networks - ICANN. Unidade: IFSC
Assuntos: COMUNICAÇÃO, ROBÓTICA, LINGUAGEM, COGNIÇÃO, REDES NEURAIS, TEORIA DE CAMPOS
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ABNT
TIKHANOFF, Vadim et al. Language and cognition integration through modeling field theory: category formation for symbol grounding. Lecture Notes in Computer Science. Berlin: Springer-Verlag. . Acesso em: 20 nov. 2025. , 2006
APA
Tikhanoff, V., Fontanari, J. F., Cangelosi, A., & Perlovsky, L. I. (2006). Language and cognition integration through modeling field theory: category formation for symbol grounding. Lecture Notes in Computer Science. Berlin: Springer-Verlag.
NLM
Tikhanoff V, Fontanari JF, Cangelosi A, Perlovsky LI. Language and cognition integration through modeling field theory: category formation for symbol grounding. Lecture Notes in Computer Science. 2006 ; 4131 376-385.[citado 2025 nov. 20 ]
Vancouver
Tikhanoff V, Fontanari JF, Cangelosi A, Perlovsky LI. Language and cognition integration through modeling field theory: category formation for symbol grounding. Lecture Notes in Computer Science. 2006 ; 4131 376-385.[citado 2025 nov. 20 ]

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