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Artigo de periodico
SWINN: efficient nearest neighbor search in sliding windows using graphs (2024)
Mastelini, Saulo Martiello ; Veloso, Bruno; Halford, Max; Carvalho, André Carlos Ponce de Leon Ferreira de ; Gama, João
Source: Information Fusion. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS, ALGORITMOS PARA PROCESSAMENTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MASTELINI, Saulo Martiello et al. SWINN: efficient nearest neighbor search in sliding windows using graphs. Information Fusion, v. 101, n. Ja 2024, p. 1-17, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.inffus.2023.101979. Acesso em: 08 jul. 2024.
APA
Mastelini, S. M., Veloso, B., Halford, M., Carvalho, A. C. P. de L. F. de, & Gama, J. (2024). SWINN: efficient nearest neighbor search in sliding windows using graphs. Information Fusion, 101( Ja 2024), 1-17. doi:10.1016/j.inffus.2023.101979
NLM
Mastelini SM, Veloso B, Halford M, Carvalho ACP de LF de, Gama J. SWINN: efficient nearest neighbor search in sliding windows using graphs [Internet]. Information Fusion. 2024 ; 101( Ja 2024): 1-17.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1016/j.inffus.2023.101979
Vancouver
Mastelini SM, Veloso B, Halford M, Carvalho ACP de LF de, Gama J. SWINN: efficient nearest neighbor search in sliding windows using graphs [Internet]. Information Fusion. 2024 ; 101( Ja 2024): 1-17.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1016/j.inffus.2023.101979
Artigo de periodico
Neural architecture search with interpretable meta-features and fast predictors (2023)
Pereira, Gean Trindade ; Santos, Iury Batista de Andrade ; Garcia, Luís Paulo Faina ; Urruty, Thierry ; Visani, Muriel ; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Information Sciences. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS
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ABNT
PEREIRA, Gean Trindade et al. Neural architecture search with interpretable meta-features and fast predictors. Information Sciences, v. No 2023, p. 1-17, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2023.119642. Acesso em: 08 jul. 2024.
APA
Pereira, G. T., Santos, I. B. de A., Garcia, L. P. F., Urruty, T., Visani, M., & Carvalho, A. C. P. de L. F. de. (2023). Neural architecture search with interpretable meta-features and fast predictors. Information Sciences, No 2023, 1-17. doi:10.1016/j.ins.2023.119642
NLM
Pereira GT, Santos IB de A, Garcia LPF, Urruty T, Visani M, Carvalho ACP de LF de. Neural architecture search with interpretable meta-features and fast predictors [Internet]. Information Sciences. 2023 ; No 2023 1-17.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1016/j.ins.2023.119642
Vancouver
Pereira GT, Santos IB de A, Garcia LPF, Urruty T, Visani M, Carvalho ACP de LF de. Neural architecture search with interpretable meta-features and fast predictors [Internet]. Information Sciences. 2023 ; No 2023 1-17.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1016/j.ins.2023.119642
Artigo de periodico
DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage (2021)
Machado, Bruno Brandoli ; Spadon, Gabriel ; Esau, Travis ; Hennessy, Patrick ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Amer-Yahia, Sihem ; Rodrigues Junior, José Fernando
Source: Computers and Electronics in Agriculture. Unidade: ICMC
Subjects: COMPUTAÇÃO MÓVEL, PROCESSAMENTO DE IMAGENS, AGRICULTURA DE PRECISÃO, PESTICIDAS
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ABNT
MACHADO, Bruno Brandoli et al. DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage. Computers and Electronics in Agriculture, v. 180, n. Ja 2021, p. 1-9, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2020.105906. Acesso em: 08 jul. 2024.
APA
Machado, B. B., Spadon, G., Esau, T., Hennessy, P., Carvalho, A. C. P. de L. F. de, Amer-Yahia, S., & Rodrigues Junior, J. F. (2021). DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage. Computers and Electronics in Agriculture, 180( Ja 2021), 1-9. doi:10.1016/j.compag.2020.105906
NLM
Machado BB, Spadon G, Esau T, Hennessy P, Carvalho ACP de LF de, Amer-Yahia S, Rodrigues Junior JF. DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage [Internet]. Computers and Electronics in Agriculture. 2021 ; 180( Ja 2021): 1-9.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1016/j.compag.2020.105906
Vancouver
Machado BB, Spadon G, Esau T, Hennessy P, Carvalho ACP de LF de, Amer-Yahia S, Rodrigues Junior JF. DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage [Internet]. Computers and Electronics in Agriculture. 2021 ; 180( Ja 2021): 1-9.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1016/j.compag.2020.105906
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
Source: Lecture Notes in Computer Science. Conference titles: International Conference on Artificial Neural Networks - ICANN. Unidade: ICMC
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, REDES NEURAIS, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 08 jul. 2024. , 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 2024 jul. 08 ] 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 2024 jul. 08 ] Available from: https://doi.org/10.1007/978-3-030-86383-8_10
Artigo de periodico
Assessing the data complexity of imbalanced datasets (2021)
Barella, Victor Hugo ; Garcia, Luís Paulo Faina ; Souto, Marcílio Carlos Pereira de ; Lorena, Ana Carolina ; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Information Sciences. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, MATEMÁTICA DA COMPUTAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BARELLA, Victor Hugo et al. Assessing the data complexity of imbalanced datasets. Information Sciences, v. 553, p. 83-109, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2020.12.006. Acesso em: 08 jul. 2024.
APA
Barella, V. H., Garcia, L. P. F., Souto, M. C. P. de, Lorena, A. C., & Carvalho, A. C. P. de L. F. de. (2021). Assessing the data complexity of imbalanced datasets. Information Sciences, 553, 83-109. doi:10.1016/j.ins.2020.12.006
NLM
Barella VH, Garcia LPF, Souto MCP de, Lorena AC, Carvalho ACP de LF de. Assessing the data complexity of imbalanced datasets [Internet]. Information Sciences. 2021 ; 553 83-109.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1016/j.ins.2020.12.006
Vancouver
Barella VH, Garcia LPF, Souto MCP de, Lorena AC, Carvalho ACP de LF de. Assessing the data complexity of imbalanced datasets [Internet]. Information Sciences. 2021 ; 553 83-109.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1016/j.ins.2020.12.006
Artigo de periodico
An empirical analysis of binary transformation strategies and base algorithms for multi-label learning (2020)
Rivolli, Adriano ; Read, Jesse; Soares, Carlos; Pfahringer, Bernhard ; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Machine Learning. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, ALGORITMOS ÚTEIS E ESPECÍFICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RIVOLLI, Adriano et al. An empirical analysis of binary transformation strategies and base algorithms for multi-label learning. Machine Learning, v. 109, n. 8, p. 1509-1563, 2020Tradução . . Disponível em: https://doi.org/10.1007/s10994-020-05879-3. Acesso em: 08 jul. 2024.
APA
Rivolli, A., Read, J., Soares, C., Pfahringer, B., & Carvalho, A. C. P. de L. F. de. (2020). An empirical analysis of binary transformation strategies and base algorithms for multi-label learning. Machine Learning, 109( 8), 1509-1563. doi:10.1007/s10994-020-05879-3
NLM
Rivolli A, Read J, Soares C, Pfahringer B, Carvalho ACP de LF de. An empirical analysis of binary transformation strategies and base algorithms for multi-label learning [Internet]. Machine Learning. 2020 ; 109( 8): 1509-1563.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1007/s10994-020-05879-3
Vancouver
Rivolli A, Read J, Soares C, Pfahringer B, Carvalho ACP de LF de. An empirical analysis of binary transformation strategies and base algorithms for multi-label learning [Internet]. Machine Learning. 2020 ; 109( 8): 1509-1563.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1007/s10994-020-05879-3
Artigo de periodico
Adaptive biometric systems: review and perspectives (2019)
Pisani, Paulo Henrique ; Mhenni, Abir ; Giot, Romain ; Cherrier, Estelle; Poh, Norman ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Rosenberger, Christophe ; Amara, Najoua Essoukri Ben
Source: ACM Computing Surveys. Unidade: ICMC
Subjects: SEGURANÇA DE COMPUTADORES, RECONHECIMENTO DE PADRÕES, APRENDIZADO COMPUTACIONAL, BIOMETRIA
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ABNT
PISANI, Paulo Henrique et al. Adaptive biometric systems: review and perspectives. ACM Computing Surveys, v. 52, n. 5, p. Se 2019, 2019Tradução . . Disponível em: https://doi.org/10.1145/3344255. Acesso em: 08 jul. 2024.
APA
Pisani, P. H., Mhenni, A., Giot, R., Cherrier, E., Poh, N., Carvalho, A. C. P. de L. F. de, et al. (2019). Adaptive biometric systems: review and perspectives. ACM Computing Surveys, 52( 5), Se 2019. doi:10.1145/3344255
NLM
Pisani PH, Mhenni A, Giot R, Cherrier E, Poh N, Carvalho ACP de LF de, Rosenberger C, Amara NEB. Adaptive biometric systems: review and perspectives [Internet]. ACM Computing Surveys. 2019 ; 52( 5): Se 2019.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1145/3344255
Vancouver
Pisani PH, Mhenni A, Giot R, Cherrier E, Poh N, Carvalho ACP de LF de, Rosenberger C, Amara NEB. Adaptive biometric systems: review and perspectives [Internet]. ACM Computing Surveys. 2019 ; 52( 5): Se 2019.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1145/3344255
Artigo de periodico
Machine learning meets genome assembly (2019)
Souza, Kleber Padovani de; Setubal, Joao Carlos ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Oliveira, Guilherme; Chateau, Annie; Alves, Ronnie
Source: Briefings in Bioinformatics. Unidades: IQ, ICMC
Subjects: APRENDIZADO COMPUTACIONAL, SEQUENCIAMENTO GENÉTICO
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ABNT
SOUZA, Kleber Padovani de et al. Machine learning meets genome assembly. Briefings in Bioinformatics, v. No 2019, n. 6, p. 2116-2129, 2019Tradução . . Disponível em: https://doi.org/10.1093/bib/bby072. Acesso em: 08 jul. 2024.
APA
Souza, K. P. de, Setubal, J. C., Carvalho, A. C. P. de L. F. de, Oliveira, G., Chateau, A., & Alves, R. (2019). Machine learning meets genome assembly. Briefings in Bioinformatics, No 2019( 6), 2116-2129. doi:10.1093/bib/bby072
NLM
Souza KP de, Setubal JC, Carvalho ACP de LF de, Oliveira G, Chateau A, Alves R. Machine learning meets genome assembly [Internet]. Briefings in Bioinformatics. 2019 ; No 2019( 6): 2116-2129.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1093/bib/bby072
Vancouver
Souza KP de, Setubal JC, Carvalho ACP de LF de, Oliveira G, Chateau A, Alves R. Machine learning meets genome assembly [Internet]. Briefings in Bioinformatics. 2019 ; No 2019( 6): 2116-2129.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1093/bib/bby072
Parte de monografia/livro-apres/pref/posf
Although Machine Learning is currently a hot topic... [Prefácio] (2018)
Bifet, Albert; Carvalho, André Carlos Ponce de Leon Ferreira de ; Gama, João
Source: Machine learning : a practical approach on the statistical learning theory. Unidade: ICMC
Assunto: APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BIFET, Albert e CARVALHO, André Carlos Ponce de Leon Ferreira de e GAMA, João. Although Machine Learning is currently a hot topic.. [Prefácio]. Machine learning : a practical approach on the statistical learning theory. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-94989-5. Acesso em: 08 jul. 2024. , 2018
APA
Bifet, A., Carvalho, A. C. P. de L. F. de, & Gama, J. (2018). Although Machine Learning is currently a hot topic.. [Prefácio]. Machine learning : a practical approach on the statistical learning theory. Cham: Springer. doi:10.1007/978-3-319-94989-5
NLM
Bifet A, Carvalho ACP de LF de, Gama J. Although Machine Learning is currently a hot topic.. [Prefácio] [Internet]. Machine learning : a practical approach on the statistical learning theory. 2018 ;[citado 2024 jul. 08 ] Available from: https://doi.org/10.1007/978-3-319-94989-5
Vancouver
Bifet A, Carvalho ACP de LF de, Gama J. Although Machine Learning is currently a hot topic.. [Prefácio] [Internet]. Machine learning : a practical approach on the statistical learning theory. 2018 ;[citado 2024 jul. 08 ] Available from: https://doi.org/10.1007/978-3-319-94989-5
Trabalho de evento
Data complexity measures for imbalanced classification tasks (2018)
Barella, Victor H; Garcia, Luís P. F; Souto, Marcílio P. de; Lorena, Ana Carolina; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidade: ICMC
Subjects: RECONHECIMENTO DE PADRÕES, ALGORITMOS ÚTEIS E ESPECÍFICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BARELLA, Victor H et al. Data complexity measures for imbalanced classification tasks. 2018, Anais.. Piscataway: IEEE, 2018. Disponível em: https://doi.org/10.1109/IJCNN.2018.8489661. Acesso em: 08 jul. 2024.
APA
Barella, V. H., Garcia, L. P. F., Souto, M. P. de, Lorena, A. C., & Carvalho, A. C. P. de L. F. de. (2018). Data complexity measures for imbalanced classification tasks. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN.2018.8489661
NLM
Barella VH, Garcia LPF, Souto MP de, Lorena AC, Carvalho ACP de LF de. Data complexity measures for imbalanced classification tasks [Internet]. Proceedings. 2018 ;[citado 2024 jul. 08 ] Available from: https://doi.org/10.1109/IJCNN.2018.8489661
Vancouver
Barella VH, Garcia LPF, Souto MP de, Lorena AC, Carvalho ACP de LF de. Data complexity measures for imbalanced classification tasks [Internet]. Proceedings. 2018 ;[citado 2024 jul. 08 ] Available from: https://doi.org/10.1109/IJCNN.2018.8489661
Artigo de periodico
Enhanced template update: application to keystroke dynamics (2016)
Pisani, Paulo Henrique; Giot, Romain; Carvalho, André Carlos Ponce de Leon Ferreira de ; Lorena, Ana Carolina
Source: Computers and Security. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, RECONHECIMENTO DE PADRÕES
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ABNT
PISANI, Paulo Henrique et al. Enhanced template update: application to keystroke dynamics. Computers and Security, v. 60, p. 134-153, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.cose.2016.04.004. Acesso em: 08 jul. 2024.
APA
Pisani, P. H., Giot, R., Carvalho, A. C. P. de L. F. de, & Lorena, A. C. (2016). Enhanced template update: application to keystroke dynamics. Computers and Security, 60, 134-153. doi:10.1016/j.cose.2016.04.004
NLM
Pisani PH, Giot R, Carvalho ACP de LF de, Lorena AC. Enhanced template update: application to keystroke dynamics [Internet]. Computers and Security. 2016 ; 60 134-153.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1016/j.cose.2016.04.004
Vancouver
Pisani PH, Giot R, Carvalho ACP de LF de, Lorena AC. Enhanced template update: application to keystroke dynamics [Internet]. Computers and Security. 2016 ; 60 134-153.[citado 2024 jul. 08 ] Available from: https://doi.org/10.1016/j.cose.2016.04.004

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