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Trabalho de evento-anais periodico
Exploring text decoding methods for portuguese legal text generation (2023)
Sakiyama, Kenzo ; Montanari, Raphael ; Malaquias Junior, Roseval Donisete ; Nogueira, Rodrigo Frassetto ; Romero, Roseli Aparecida Francelin
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: ICMC, EESC
Assuntos: PROCESSAMENTO DE LINGUAGEM NATURAL, TRATAMENTO AUTOMÁTICO DE TEXTOS E DISCURSOS, RECUPERAÇÃO DA INFORMAÇÃO, PORTUGUÊS DO BRASIL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SAKIYAMA, Kenzo et al. Exploring text decoding methods for portuguese legal text generation. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-45368-7_5. Acesso em: 05 nov. 2025. , 2023
APA
Sakiyama, K., Montanari, R., Malaquias Junior, R. D., Nogueira, R. F., & Romero, R. A. F. (2023). Exploring text decoding methods for portuguese legal text generation. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-45368-7_5
NLM
Sakiyama K, Montanari R, Malaquias Junior RD, Nogueira RF, Romero RAF. Exploring text decoding methods for portuguese legal text generation [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14195 63-77.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-031-45368-7_5
Vancouver
Sakiyama K, Montanari R, Malaquias Junior RD, Nogueira RF, Romero RAF. Exploring text decoding methods for portuguese legal text generation [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14195 63-77.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-031-45368-7_5
Trabalho de evento-anais periodico
Model performance prediction: a meta-learning approach for concept drift detection (2023)
Melo, Fernanda Amaral ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Lorena, Ana Carolina ; Garcia, Luís Paulo Faina
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: International Conference on Hybrid Artificial Intelligence Systems - HAIS. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS)
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ABNT
MELO, Fernanda Amaral et al. Model performance prediction: a meta-learning approach for concept drift detection. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-40725-3_5. Acesso em: 05 nov. 2025. , 2023
APA
Melo, F. A., Carvalho, A. C. P. de L. F. de, Lorena, A. C., & Garcia, L. P. F. (2023). Model performance prediction: a meta-learning approach for concept drift detection. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-40725-3_5
NLM
Melo FA, Carvalho ACP de LF de, Lorena AC, Garcia LPF. Model performance prediction: a meta-learning approach for concept drift detection [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14001 51-62.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-031-40725-3_5
Vancouver
Melo FA, Carvalho ACP de LF de, Lorena AC, Garcia LPF. Model performance prediction: a meta-learning approach for concept drift detection [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14001 51-62.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-031-40725-3_5
Trabalho de evento-anais periodico
Regulation and ethics of facial recognition systems: an analysis of cases in the Court of Appeal in the state of São Paulo (2023)
Oliveira, Cristina Godoy Bernardo de ; Albuquerque, Otávio de Paula ; Belotti, Emily Liene; Lopes, Isabella Ferreira; Silva, Rodrigo Brandão de Andrade e; Arbix, Glauco Antonio Truzzi
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: FDRP, FFLCH, EESC E ICMC, EACH
Assuntos: RECONHECIMENTO DE IMAGEM, MINERAÇÃO DE DADOS, DIREITO DO CONSUMIDOR, JURISPRUDÊNCIA, CRÉDITO BANCÁRIO
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ABNT
OLIVEIRA, Cristina Godoy Bernardo de et al. Regulation and ethics of facial recognition systems: an analysis of cases in the Court of Appeal in the state of São Paulo. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-45368-7_2. Acesso em: 05 nov. 2025. , 2023
APA
Oliveira, C. G. B. de, Albuquerque, O. de P., Belotti, E. L., Lopes, I. F., Silva, R. B. de A. e, & Arbix, G. A. T. (2023). Regulation and ethics of facial recognition systems: an analysis of cases in the Court of Appeal in the state of São Paulo. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-45368-7_2
NLM
Oliveira CGB de, Albuquerque O de P, Belotti EL, Lopes IF, Silva RB de A e, Arbix GAT. Regulation and ethics of facial recognition systems: an analysis of cases in the Court of Appeal in the state of São Paulo [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14195 18-32.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-031-45368-7_2
Vancouver
Oliveira CGB de, Albuquerque O de P, Belotti EL, Lopes IF, Silva RB de A e, Arbix GAT. Regulation and ethics of facial recognition systems: an analysis of cases in the Court of Appeal in the state of São Paulo [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14195 18-32.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-031-45368-7_2
Trabalho de evento-anais periodico
A network-based visual analytics approach for performance evaluation of swarms of robots in the surveillance task (2022)
Linhares, Claudio Douglas Gouveia ; Tinoco, Claudiney Ramos ; Ponciano, Jean Roberto ; Oliveira, Gina Maira Barbosa de; Travençolo, Bruno Augusto Nassif
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: ROBÓTICA, VISÃO COMPUTACIONAL, VISUALIZAÇÃO, REDES COMPLEXAS
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ABNT
LINHARES, Claudio Douglas Gouveia et al. A network-based visual analytics approach for performance evaluation of swarms of robots in the surveillance task. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-21686-2_5. Acesso em: 05 nov. 2025. , 2022
APA
Linhares, C. D. G., Tinoco, C. R., Ponciano, J. R., Oliveira, G. M. B. de, & Travençolo, B. A. N. (2022). A network-based visual analytics approach for performance evaluation of swarms of robots in the surveillance task. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-21686-2_5
NLM
Linhares CDG, Tinoco CR, Ponciano JR, Oliveira GMB de, Travençolo BAN. A network-based visual analytics approach for performance evaluation of swarms of robots in the surveillance task [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 61-76.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_5
Vancouver
Linhares CDG, Tinoco CR, Ponciano JR, Oliveira GMB de, Travençolo BAN. A network-based visual analytics approach for performance evaluation of swarms of robots in the surveillance task [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 61-76.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_5
Trabalho de evento-anais periodico
Geographic context-based stacking learning for election prediction from socio-economic data (2022)
Silva, Tiago Pinho da ; Parmezan, Antonio Rafael Sabino ; Batista, Gustavo Enrique de Almeida Prado Alves
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, COMPORTAMENTO ELEITORAL
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ABNT
SILVA, Tiago Pinho da e PARMEZAN, Antonio Rafael Sabino e BATISTA, Gustavo Enrique de Almeida Prado Alves. Geographic context-based stacking learning for election prediction from socio-economic data. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-21686-2_44. Acesso em: 05 nov. 2025. , 2022
APA
Silva, T. P. da, Parmezan, A. R. S., & Batista, G. E. de A. P. A. (2022). Geographic context-based stacking learning for election prediction from socio-economic data. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-21686-2_44
NLM
Silva TP da, Parmezan ARS, Batista GE de APA. Geographic context-based stacking learning for election prediction from socio-economic data [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 641-657.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_44
Vancouver
Silva TP da, Parmezan ARS, Batista GE de APA. Geographic context-based stacking learning for election prediction from socio-economic data [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 641-657.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_44
Trabalho de evento-anais periodico
Brazilian portuguese speech recognition using Wav2vec 2.0 (2022)
Gris, Lucas Rafael Stefanel ; Casanova, Edresson ; Oliveira, Frederico Santos de ; Soares, Anderson da Silva ; Candido Junior, Arnaldo
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: International Conference on Computational Processing of the Portuguese Language - PROPOR. Unidade: ICMC
Assuntos: RECONHECIMENTO DA FALA, APRENDIZADO COMPUTACIONAL, PORTUGUÊS DO BRASIL
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ABNT
GRIS, Lucas Rafael Stefanel et al. Brazilian portuguese speech recognition using Wav2vec 2.0. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-98305-5_31. Acesso em: 05 nov. 2025. , 2022
APA
Gris, L. R. S., Casanova, E., Oliveira, F. S. de, Soares, A. da S., & Candido Junior, A. (2022). Brazilian portuguese speech recognition using Wav2vec 2.0. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-98305-5_31
NLM
Gris LRS, Casanova E, Oliveira FS de, Soares A da S, Candido Junior A. Brazilian portuguese speech recognition using Wav2vec 2.0 [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13208 333-343.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-030-98305-5_31
Vancouver
Gris LRS, Casanova E, Oliveira FS de, Soares A da S, Candido Junior A. Brazilian portuguese speech recognition using Wav2vec 2.0 [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13208 333-343.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-030-98305-5_31
Trabalho de evento-anais periodico
A new genetic improvement operator based on frequency analysis for genetic algorithms applied to job shop scheduling problem (2021)
Viana, Monique Simplicio ; Contreras, Rodrigo Colnago ; Morandin Junior, Orides
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: International Conference on Artificial Intelligence and Soft Computing - ICAISC. Unidade: ICMC
Assuntos: ALGORITMOS GENÉTICOS, COMPUTAÇÃO BIOINSPIRADA, OTIMIZAÇÃO COMBINATÓRIA
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ABNT
VIANA, Monique Simplicio e CONTRERAS, Rodrigo Colnago e MORANDIN JUNIOR, Orides. A new genetic improvement operator based on frequency analysis for genetic algorithms applied to job shop scheduling problem. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-87986-0_39. Acesso em: 05 nov. 2025. , 2021
APA
Viana, M. S., Contreras, R. C., & Morandin Junior, O. (2021). A new genetic improvement operator based on frequency analysis for genetic algorithms applied to job shop scheduling problem. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-87986-0_39
NLM
Viana MS, Contreras RC, Morandin Junior O. A new genetic improvement operator based on frequency analysis for genetic algorithms applied to job shop scheduling problem [Internet]. Lecture Notes in Artificial Intelligence. 2021 ; 12854 434-450.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-030-87986-0_39
Vancouver
Viana MS, Contreras RC, Morandin Junior O. A new genetic improvement operator based on frequency analysis for genetic algorithms applied to job shop scheduling problem [Internet]. Lecture Notes in Artificial Intelligence. 2021 ; 12854 434-450.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-030-87986-0_39
Trabalho de evento-anais periodico
A heterogeneous network-based positive and unlabeled learning approach to detect fake news (2021)
Souza, Mariana Caravanti de ; Nogueira, Bruno Magalhães ; Rossi, Rafael Geraldeli ; Marcacini, Ricardo Marcondes ; Rezende, Solange Oliveira
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: FAKE NEWS, PROCESSAMENTO DE TEXTO, APRENDIZADO COMPUTACIONAL
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ABNT
SOUZA, Mariana Caravanti de et al. A heterogeneous network-based positive and unlabeled learning approach to detect fake news. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-91699-2_1. Acesso em: 05 nov. 2025. , 2021
APA
Souza, M. C. de, Nogueira, B. M., Rossi, R. G., Marcacini, R. M., & Rezende, S. O. (2021). A heterogeneous network-based positive and unlabeled learning approach to detect fake news. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-91699-2_1
NLM
Souza MC de, Nogueira BM, Rossi RG, Marcacini RM, Rezende SO. A heterogeneous network-based positive and unlabeled learning approach to detect fake news [Internet]. Lecture Notes in Artificial Intelligence. 2021 ; 13074 3-18.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-030-91699-2_1
Vancouver
Souza MC de, Nogueira BM, Rossi RG, Marcacini RM, Rezende SO. A heterogeneous network-based positive and unlabeled learning approach to detect fake news [Internet]. Lecture Notes in Artificial Intelligence. 2021 ; 13074 3-18.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-030-91699-2_1
Trabalho de evento-anais periodico
Speech2Phone: a novel and efficient method for training speaker recognition models (2021)
Casanova, Edresson ; Candido Junior, Arnaldo ; Shulby, Christopher Dane ; Oliveira, Frederico Santos de ; Gris, Lucas Rafael Stefanel ; Silva, Hamilton Pereira da ; Aluísio, Sandra Maria ; Ponti, Moacir Antonelli
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: PROCESSAMENTO DE LINGUAGEM NATURAL, RECONHECIMENTO DE VOZ, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CASANOVA, Edresson et al. Speech2Phone: a novel and efficient method for training speaker recognition models. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-91699-2_39. Acesso em: 05 nov. 2025. , 2021
APA
Casanova, E., Candido Junior, A., Shulby, C. D., Oliveira, F. S. de, Gris, L. R. S., Silva, H. P. da, et al. (2021). Speech2Phone: a novel and efficient method for training speaker recognition models. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-91699-2_39
NLM
Casanova E, Candido Junior A, Shulby CD, Oliveira FS de, Gris LRS, Silva HP da, Aluísio SM, Ponti MA. Speech2Phone: a novel and efficient method for training speaker recognition models [Internet]. Lecture Notes in Artificial Intelligence. 2021 ; 13074 572-585.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-030-91699-2_39
Vancouver
Casanova E, Candido Junior A, Shulby CD, Oliveira FS de, Gris LRS, Silva HP da, Aluísio SM, Ponti MA. Speech2Phone: a novel and efficient method for training speaker recognition models [Internet]. Lecture Notes in Artificial Intelligence. 2021 ; 13074 572-585.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-030-91699-2_39

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