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Artigo de periodico
Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle (2024)
Ferraz, Priscila Assis ; Poit, Diego Angelo Schmidt; Pinto, Leonardo Marin Ferreira ; Guerra, Arthur Cobayashi; Laurindo Neto, Adomar ; Prado, Francisco Luiz do; Azrak, Alexandre José; Çakmakçi, Cihan; Baruselli, Pietro Sampaio ; Pugliesi, Guilherme
Fonte: Theriogenology. Unidades: FMVZ, FZEA
Assuntos: BOVINOS LEITEIROS, BIOMARCADORES, PRENHEZ, APRENDIZADO COMPUTACIONAL
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FERRAZ, Priscila Assis et al. Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle. Theriogenology, v. 224, p. 82-93, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.theriogenology.2024.05.006. Acesso em: 27 jun. 2024.
APA
Ferraz, P. A., Poit, D. A. S., Pinto, L. M. F., Guerra, A. C., Laurindo Neto, A., Prado, F. L. do, et al. (2024). Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle. Theriogenology, 224, 82-93. doi:10.1016/j.theriogenology.2024.05.006
NLM
Ferraz PA, Poit DAS, Pinto LMF, Guerra AC, Laurindo Neto A, Prado FL do, Azrak AJ, Çakmakçi C, Baruselli PS, Pugliesi G. Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle [Internet]. Theriogenology. 2024 ; 224 82-93.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.theriogenology.2024.05.006
Vancouver
Ferraz PA, Poit DAS, Pinto LMF, Guerra AC, Laurindo Neto A, Prado FL do, Azrak AJ, Çakmakçi C, Baruselli PS, Pugliesi G. Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle [Internet]. Theriogenology. 2024 ; 224 82-93.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.theriogenology.2024.05.006
Artigo de periodico
DODFMiner: an automated tool for named entity recognition from Official Gazettes (2024)
Guimarães, Gabriel Mendes Ciriatico; Silva, Felipe X. Barbosa da; Queiroz, Andrei Lima ; Marcacini, Ricardo Marcondes ; Faleiros, Thiago de Paulo ; Borges, Vinicius Ruela Pereira ; Garcia, Luís Paulo Faina
Fonte: Neurocomputing. Unidade: ICMC
Assuntos: PROCESSAMENTO DE LINGUAGEM NATURAL, TRATAMENTO AUTOMÁTICO DE TEXTOS E DISCURSOS, RECONHECIMENTO DE TEXTO, APRENDIZADO COMPUTACIONAL
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GUIMARÃES, Gabriel Mendes Ciriatico et al. DODFMiner: an automated tool for named entity recognition from Official Gazettes. Neurocomputing, v. 568, p. 1-12, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2023.127064. Acesso em: 27 jun. 2024.
APA
Guimarães, G. M. C., Silva, F. X. B. da, Queiroz, A. L., Marcacini, R. M., Faleiros, T. de P., Borges, V. R. P., & Garcia, L. P. F. (2024). DODFMiner: an automated tool for named entity recognition from Official Gazettes. Neurocomputing, 568, 1-12. doi:10.1016/j.neucom.2023.127064
NLM
Guimarães GMC, Silva FXB da, Queiroz AL, Marcacini RM, Faleiros T de P, Borges VRP, Garcia LPF. DODFMiner: an automated tool for named entity recognition from Official Gazettes [Internet]. Neurocomputing. 2024 ; 568 1-12.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.neucom.2023.127064
Vancouver
Guimarães GMC, Silva FXB da, Queiroz AL, Marcacini RM, Faleiros T de P, Borges VRP, Garcia LPF. DODFMiner: an automated tool for named entity recognition from Official Gazettes [Internet]. Neurocomputing. 2024 ; 568 1-12.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.neucom.2023.127064
Artigo de periodico
Coarsening algorithm based on multi-label propagation for knowledge discovery in bipartite networks (2024)
Valejo, Alan Demetrius Baria ; Althoff, Paulo Eduardo ; Faleiros, Thiago de Paulo ; Rocha Filho, Geraldo Pereira ; Yu-Tao, Zhu ; Jianglong, Yan; Weiguang, Liu; Liang, Zhao
Fonte: IEEE Transactions on Network Science and Engineering. Unidades: FFCLRP, ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, DESCOBERTA DE CONHECIMENTO, ALGORITMOS ÚTEIS E ESPECÍFICOS, REDES COMPLEXAS
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VALEJO, Alan Demetrius Baria et al. Coarsening algorithm based on multi-label propagation for knowledge discovery in bipartite networks. IEEE Transactions on Network Science and Engineering, v. 11, n. 2, p. 1799-1809, 2024Tradução . . Disponível em: https://doi.org/10.1109/TNSE.2023.3331655. Acesso em: 27 jun. 2024.
APA
Valejo, A. D. B., Althoff, P. E., Faleiros, T. de P., Rocha Filho, G. P., Yu-Tao, Z., Jianglong, Y., et al. (2024). Coarsening algorithm based on multi-label propagation for knowledge discovery in bipartite networks. IEEE Transactions on Network Science and Engineering, 11( 2), 1799-1809. doi:10.1109/TNSE.2023.3331655
NLM
Valejo ADB, Althoff PE, Faleiros T de P, Rocha Filho GP, Yu-Tao Z, Jianglong Y, Weiguang L, Liang Z. Coarsening algorithm based on multi-label propagation for knowledge discovery in bipartite networks [Internet]. IEEE Transactions on Network Science and Engineering. 2024 ; 11( 2): 1799-1809.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1109/TNSE.2023.3331655
Vancouver
Valejo ADB, Althoff PE, Faleiros T de P, Rocha Filho GP, Yu-Tao Z, Jianglong Y, Weiguang L, Liang Z. Coarsening algorithm based on multi-label propagation for knowledge discovery in bipartite networks [Internet]. IEEE Transactions on Network Science and Engineering. 2024 ; 11( 2): 1799-1809.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1109/TNSE.2023.3331655
Artigo de periodico
On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments (2024)
Alves, Caroline Lourenço ; Ciba, Manuel ; Toutain, Thaise Graziele Lima de ; Porto, Joel Augusto Moura ; Sena, Eduardo Pondé de ; Thielemann, Christiane ; Rodrigues, Francisco
Fonte: Journal of Physics: Complexity. Unidades: ICMC, IFSC
Assuntos: VISÃO COMPUTACIONAL, APRENDIZADO COMPUTACIONAL, TOPOLOGIA EM COMPUTAÇÃO, REDES NEURAIS, TEORIA DOS GRAFOS, CÓRTEX CEREBRAL (ANÁLISE), CÉREBRO (ANÁLISE;ESTUDO)
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ALVES, Caroline Lourenço et al. On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments. Journal of Physics: Complexity, v. 5, n. Ja 2024, p. 015002-1-015002-23, 2024Tradução . . Disponível em: https://doi.org/10.1088/2632-072X/ad1c68. Acesso em: 27 jun. 2024.
APA
Alves, C. L., Ciba, M., Toutain, T. G. L. de, Porto, J. A. M., Sena, E. P. de, Thielemann, C., & Rodrigues, F. (2024). On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments. Journal of Physics: Complexity, 5( Ja 2024), 015002-1-015002-23. doi:10.1088/2632-072X/ad1c68
NLM
Alves CL, Ciba M, Toutain TGL de, Porto JAM, Sena EP de, Thielemann C, Rodrigues F. On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments [Internet]. Journal of Physics: Complexity. 2024 ; 5( Ja 2024): 015002-1-015002-23.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1088/2632-072X/ad1c68
Vancouver
Alves CL, Ciba M, Toutain TGL de, Porto JAM, Sena EP de, Thielemann C, Rodrigues F. On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments [Internet]. Journal of Physics: Complexity. 2024 ; 5( Ja 2024): 015002-1-015002-23.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1088/2632-072X/ad1c68
Artigo de periodico
Driven electron g-factor anisotropy in layered III–V semiconductors: interfacing, tunnel coupling, and structure inversion asymmetry effects (2024)
Sandoval, Marcelo Alejandro Toloza ; Padilla, Jhon Elber Leon ; Wanderley, Adilson Barros ; Sipahi, Guilherme Matos ; Chubaci, José Fernando Diniz ; Silva, Antonio Ferreira da
Fonte: Journal of Applied Physics. Unidades: IFSC, IF
Assuntos: APRENDIZADO COMPUTACIONAL, SEMICONDUTORES
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SANDOVAL, Marcelo Alejandro Toloza et al. Driven electron g-factor anisotropy in layered III–V semiconductors: interfacing, tunnel coupling, and structure inversion asymmetry effects. Journal of Applied Physics, v. 135, n. 10, p. 103901-1-103901-9, 2024Tradução . . Disponível em: https://doi.org/10.1063/5.0187962. Acesso em: 27 jun. 2024.
APA
Sandoval, M. A. T., Padilla, J. E. L., Wanderley, A. B., Sipahi, G. M., Chubaci, J. F. D., & Silva, A. F. da. (2024). Driven electron g-factor anisotropy in layered III–V semiconductors: interfacing, tunnel coupling, and structure inversion asymmetry effects. Journal of Applied Physics, 135( 10), 103901-1-103901-9. doi:10.1063/5.0187962
NLM
Sandoval MAT, Padilla JEL, Wanderley AB, Sipahi GM, Chubaci JFD, Silva AF da. Driven electron g-factor anisotropy in layered III–V semiconductors: interfacing, tunnel coupling, and structure inversion asymmetry effects [Internet]. Journal of Applied Physics. 2024 ; 135( 10): 103901-1-103901-9.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1063/5.0187962
Vancouver
Sandoval MAT, Padilla JEL, Wanderley AB, Sipahi GM, Chubaci JFD, Silva AF da. Driven electron g-factor anisotropy in layered III–V semiconductors: interfacing, tunnel coupling, and structure inversion asymmetry effects [Internet]. Journal of Applied Physics. 2024 ; 135( 10): 103901-1-103901-9.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1063/5.0187962
Artigo de periodico
Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection (2024)
Pazin, Wallance Moreira ; Furini, Leonardo Negri; Braz, Daniel César ; Popolin Neto, Mário ; Fernandes, José Diego ; Constantino, Carlos José Leopoldo ; Oliveira Junior, Osvaldo Novais de
Fonte: ACS Applied Nano Materials. Unidades: IFSC, ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, COVID-19, EFEITO RAMAN
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PAZIN, Wallance Moreira et al. Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection. ACS Applied Nano Materials, v. 7, n. Ja 2024, p. 2335-2342, 2024Tradução . . Disponível em: https://doi.org/10.1021/acsanm.3c05848. Acesso em: 27 jun. 2024.
APA
Pazin, W. M., Furini, L. N., Braz, D. C., Popolin Neto, M., Fernandes, J. D., Constantino, C. J. L., & Oliveira Junior, O. N. de. (2024). Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection. ACS Applied Nano Materials, 7( Ja 2024), 2335-2342. doi:10.1021/acsanm.3c05848
NLM
Pazin WM, Furini LN, Braz DC, Popolin Neto M, Fernandes JD, Constantino CJL, Oliveira Junior ON de. Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection [Internet]. ACS Applied Nano Materials. 2024 ; 7( Ja 2024): 2335-2342.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1021/acsanm.3c05848
Vancouver
Pazin WM, Furini LN, Braz DC, Popolin Neto M, Fernandes JD, Constantino CJL, Oliveira Junior ON de. Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection [Internet]. ACS Applied Nano Materials. 2024 ; 7( Ja 2024): 2335-2342.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1021/acsanm.3c05848
Artigo de periodico
Electronic tongue made of gelatin self-supporting films on printed electrodes to detect lactose (2024)
Piccinin, Ana C. V.; Soares, Andrey Coatrini ; Franco, Giuliana Thalina ; Bondancia, Thalita Jessika ; Soares, Juliana Coatrini ; Oliveira Junior, Osvaldo Novais de ; Mattoso, Luiz Henrique Capparelli
Fonte: Frontiers in Sensors. Unidade: IFSC
Assuntos: SENSOR, MONITORAMENTO AMBIENTAL, APRENDIZADO COMPUTACIONAL, SENSORES BIOMÉDICOS, FILMES, PECUÁRIA LEITEIRA
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PICCININ, Ana C. V. et al. Electronic tongue made of gelatin self-supporting films on printed electrodes to detect lactose. Frontiers in Sensors, v. 5, 2024Tradução . . Disponível em: https://doi.org/10.3389/fsens.2024.1401077. Acesso em: 27 jun. 2024.
APA
Piccinin, A. C. V., Soares, A. C., Franco, G. T., Bondancia, T. J., Soares, J. C., Oliveira Junior, O. N. de, & Mattoso, L. H. C. (2024). Electronic tongue made of gelatin self-supporting films on printed electrodes to detect lactose. Frontiers in Sensors, 5. doi:10.3389/fsens.2024.1401077
NLM
Piccinin ACV, Soares AC, Franco GT, Bondancia TJ, Soares JC, Oliveira Junior ON de, Mattoso LHC. Electronic tongue made of gelatin self-supporting films on printed electrodes to detect lactose [Internet]. Frontiers in Sensors. 2024 ; 5[citado 2024 jun. 27 ] Available from: https://doi.org/10.3389/fsens.2024.1401077
Vancouver
Piccinin ACV, Soares AC, Franco GT, Bondancia TJ, Soares JC, Oliveira Junior ON de, Mattoso LHC. Electronic tongue made of gelatin self-supporting films on printed electrodes to detect lactose [Internet]. Frontiers in Sensors. 2024 ; 5[citado 2024 jun. 27 ] Available from: https://doi.org/10.3389/fsens.2024.1401077
Artigo de periodico
BioPrediction-RPI: democratizing the prediction of interaction between non-coding RNA and protein with end-to-end machine learning (2024)
Florentino, Bruno Rafael ; Bonidia, Robson Parmezan ; Sanches, Natan Henrique ; Rocha, Ulisses Nunes da ; Carvalho, Andre Carlos Ponce de Leon Ferreira de
Fonte: Computational and Structural Biotechnology Journal. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, ALGORITMOS ÚTEIS E ESPECÍFICOS, BIOINFORMÁTICA, GENÔMICA
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FLORENTINO, Bruno Rafael et al. BioPrediction-RPI: democratizing the prediction of interaction between non-coding RNA and protein with end-to-end machine learning. Computational and Structural Biotechnology Journal, v. 23, p. 2267-2276, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.csbj.2024.05.031. Acesso em: 27 jun. 2024.
APA
Florentino, B. R., Bonidia, R. P., Sanches, N. H., Rocha, U. N. da, & Carvalho, A. C. P. de L. F. de. (2024). BioPrediction-RPI: democratizing the prediction of interaction between non-coding RNA and protein with end-to-end machine learning. Computational and Structural Biotechnology Journal, 23, 2267-2276. doi:10.1016/j.csbj.2024.05.031
NLM
Florentino BR, Bonidia RP, Sanches NH, Rocha UN da, Carvalho ACP de LF de. BioPrediction-RPI: democratizing the prediction of interaction between non-coding RNA and protein with end-to-end machine learning [Internet]. Computational and Structural Biotechnology Journal. 2024 ; 23 2267-2276.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.csbj.2024.05.031
Vancouver
Florentino BR, Bonidia RP, Sanches NH, Rocha UN da, Carvalho ACP de LF de. BioPrediction-RPI: democratizing the prediction of interaction between non-coding RNA and protein with end-to-end machine learning [Internet]. Computational and Structural Biotechnology Journal. 2024 ; 23 2267-2276.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.csbj.2024.05.031
Artigo de periodico
Corrigendum to: "Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals" [Comput. Electron. Agric. 216 (2024) 108502] (2024)
Silveira, Robson Mateus Freitas ; Façanha, Débora Andréa Evangelista; McManus, Concepta; Bermejo Asensio, Luis Alberto; Silva, Iran José Oliveira da
Fonte: Computers and Electronics in Agriculture. Unidade: ESALQ
Assuntos: ADAPTAÇÃO ANIMAL, ALGORITMOS, APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL, PRODUÇÃO ANIMAL, REGULAÇÃO DA TEMPERATURA CORPORAL ANIMAL, SENSOR
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SILVEIRA, Robson Mateus Freitas et al. Corrigendum to: "Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals" [Comput. Electron. Agric. 216 (2024) 108502]. Computers and Electronics in Agriculture, v. 218, p. 1, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2024.108673. Acesso em: 27 jun. 2024.
APA
Silveira, R. M. F., Façanha, D. A. E., McManus, C., Bermejo Asensio, L. A., & Silva, I. J. O. da. (2024). Corrigendum to: "Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals" [Comput. Electron. Agric. 216 (2024) 108502]. Computers and Electronics in Agriculture, 218, 1. doi:10.1016/j.compag.2024.108673
NLM
Silveira RMF, Façanha DAE, McManus C, Bermejo Asensio LA, Silva IJO da. Corrigendum to: "Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals" [Comput. Electron. Agric. 216 (2024) 108502] [Internet]. Computers and Electronics in Agriculture. 2024 ; 218 1.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.compag.2024.108673
Vancouver
Silveira RMF, Façanha DAE, McManus C, Bermejo Asensio LA, Silva IJO da. Corrigendum to: "Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals" [Comput. Electron. Agric. 216 (2024) 108502] [Internet]. Computers and Electronics in Agriculture. 2024 ; 218 1.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.compag.2024.108673
Artigo de periodico
Enhancing elemental quantification in LIBS with SHAP-guided emission line analysis: a soil carbon study (2024)
Neiva, Davi Keglevich; Guedes, Wesley Nascimento ; Martin-Neto, Ladislau ; Villas Boas, Paulino Ribeiro
Fonte: Spectrochimica Acta Part B : Atomic Spectroscopy. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, ESPECTROSCOPIA, ANÁLISE DO SOLO, CARBONO
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NEIVA, Davi Keglevich et al. Enhancing elemental quantification in LIBS with SHAP-guided emission line analysis: a soil carbon study. Spectrochimica Acta Part B : Atomic Spectroscopy, v. 217, p. 1-8, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.sab.2024.106971. Acesso em: 27 jun. 2024.
APA
Neiva, D. K., Guedes, W. N., Martin-Neto, L., & Villas Boas, P. R. (2024). Enhancing elemental quantification in LIBS with SHAP-guided emission line analysis: a soil carbon study. Spectrochimica Acta Part B : Atomic Spectroscopy, 217, 1-8. doi:10.1016/j.sab.2024.106971
NLM
Neiva DK, Guedes WN, Martin-Neto L, Villas Boas PR. Enhancing elemental quantification in LIBS with SHAP-guided emission line analysis: a soil carbon study [Internet]. Spectrochimica Acta Part B : Atomic Spectroscopy. 2024 ; 217 1-8.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.sab.2024.106971
Vancouver
Neiva DK, Guedes WN, Martin-Neto L, Villas Boas PR. Enhancing elemental quantification in LIBS with SHAP-guided emission line analysis: a soil carbon study [Internet]. Spectrochimica Acta Part B : Atomic Spectroscopy. 2024 ; 217 1-8.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.sab.2024.106971
Artigo de periodico
Discrimination of ingestive behavior in sheep using an electronic device based on a triaxial accelerometer and machine learning (2024)
Amorim, Magno do Nascimento; Turco, Silvia Helena Nogueira; Costa, Daniel dos Santos; Ferreira, Iara Jeanice Souza; Silva, Wedson Pereira da; Sabino, Antonio Leopoldo Cardoso ; Oliveira da Silva-Miranda, Késia
Fonte: Computers and Electronics in Agriculture. Unidade: ESALQ
Assuntos: ALIMENTAÇÃO ANIMAL, AMOSTRAGEM, APRENDIZADO COMPUTACIONAL, DISPOSITIVOS ELETRÔNICOS, INGESTÃO, INTELIGÊNCIA ARTIFICIAL, OVINOS
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AMORIM, Magno do Nascimento et al. Discrimination of ingestive behavior in sheep using an electronic device based on a triaxial accelerometer and machine learning. Computers and Electronics in Agriculture, v. 218, p. 1-8, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2024.108657. Acesso em: 27 jun. 2024.
APA
Amorim, M. do N., Turco, S. H. N., Costa, D. dos S., Ferreira, I. J. S., Silva, W. P. da, Sabino, A. L. C., & Oliveira da Silva-Miranda, K. (2024). Discrimination of ingestive behavior in sheep using an electronic device based on a triaxial accelerometer and machine learning. Computers and Electronics in Agriculture, 218, 1-8. doi:10.1016/j.compag.2024.108657
NLM
Amorim M do N, Turco SHN, Costa D dos S, Ferreira IJS, Silva WP da, Sabino ALC, Oliveira da Silva-Miranda K. Discrimination of ingestive behavior in sheep using an electronic device based on a triaxial accelerometer and machine learning [Internet]. Computers and Electronics in Agriculture. 2024 ; 218 1-8.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.compag.2024.108657
Vancouver
Amorim M do N, Turco SHN, Costa D dos S, Ferreira IJS, Silva WP da, Sabino ALC, Oliveira da Silva-Miranda K. Discrimination of ingestive behavior in sheep using an electronic device based on a triaxial accelerometer and machine learning [Internet]. Computers and Electronics in Agriculture. 2024 ; 218 1-8.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.compag.2024.108657
Artigo de periodico
Forecasting financial market structure from network features using machine learning (2024)
Castilho, Douglas; Souza, Thársis Tuani Pinto; Kang, Soong Moon; Gama, João ; Carvalho, Andre Carlos Ponce de Leon Ferreira de
Fonte: Knowledge and Information Systems. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), REDES COMPLEXAS, MERCADO FINANCEIRO
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CASTILHO, Douglas et al. Forecasting financial market structure from network features using machine learning. Knowledge and Information Systems, 2024Tradução . . Disponível em: https://doi.org/10.1007/s10115-024-02095-6. Acesso em: 27 jun. 2024.
APA
Castilho, D., Souza, T. T. P., Kang, S. M., Gama, J., & Carvalho, A. C. P. de L. F. de. (2024). Forecasting financial market structure from network features using machine learning. Knowledge and Information Systems. doi:10.1007/s10115-024-02095-6
NLM
Castilho D, Souza TTP, Kang SM, Gama J, Carvalho ACP de LF de. Forecasting financial market structure from network features using machine learning [Internet]. Knowledge and Information Systems. 2024 ;[citado 2024 jun. 27 ] Available from: https://doi.org/10.1007/s10115-024-02095-6
Vancouver
Castilho D, Souza TTP, Kang SM, Gama J, Carvalho ACP de LF de. Forecasting financial market structure from network features using machine learning [Internet]. Knowledge and Information Systems. 2024 ;[citado 2024 jun. 27 ] Available from: https://doi.org/10.1007/s10115-024-02095-6
Artigo de periodico
Evaluating YOLO architectures for detecting road killed endangered Brazilian animals (2024)
Ferrante, Gabriel Souto ; Nakamura, Luis Hideo Vasconcelos ; Sampaio, Sandra Coccuzzo ; Rocha Filho, Geraldo Pereira ; Meneguette, Rodolfo Ipolito
Fonte: Scientific Reports. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, VISÃO COMPUTACIONAL, ANIMAIS SELVAGENS, ATROPELAMENTO
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FERRANTE, Gabriel Souto et al. Evaluating YOLO architectures for detecting road killed endangered Brazilian animals. Scientific Reports, v. 14, p. 1-17, 2024Tradução . . Disponível em: https://doi.org/10.1038/s41598-024-52054-y. Acesso em: 27 jun. 2024.
APA
Ferrante, G. S., Nakamura, L. H. V., Sampaio, S. C., Rocha Filho, G. P., & Meneguette, R. I. (2024). Evaluating YOLO architectures for detecting road killed endangered Brazilian animals. Scientific Reports, 14, 1-17. doi:10.1038/s41598-024-52054-y
NLM
Ferrante GS, Nakamura LHV, Sampaio SC, Rocha Filho GP, Meneguette RI. Evaluating YOLO architectures for detecting road killed endangered Brazilian animals [Internet]. Scientific Reports. 2024 ; 14 1-17.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1038/s41598-024-52054-y
Vancouver
Ferrante GS, Nakamura LHV, Sampaio SC, Rocha Filho GP, Meneguette RI. Evaluating YOLO architectures for detecting road killed endangered Brazilian animals [Internet]. Scientific Reports. 2024 ; 14 1-17.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1038/s41598-024-52054-y
Artigo de periodico
Legal document segmentation and labeling through named entity recognition approaches (2024)
Guimarães, Gabriel Mendes Ciriatico ; Silva, Felipe Xavier Barbosa da ; Macêdo, Lucas de Almeida Bandeira ; Lisboa, Victor Hugo França ; Marcacini, Ricardo Marcondes ; Queiroz, Andrei Lima ; Borges, Vinicius Ruela Pereira ; Faleiros, Thiago de Paulo ; Garcia, Luís Paulo Faina
Fonte: Journal of Information and Data Management - JIDM. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE TEXTO, PROCESSAMENTO DE LINGUAGEM NATURAL, TRATAMENTO AUTOMÁTICO DE TEXTOS E DISCURSOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GUIMARÃES, Gabriel Mendes Ciriatico et al. Legal document segmentation and labeling through named entity recognition approaches. Journal of Information and Data Management - JIDM, v. 15, n. 1, p. 123-131, 2024Tradução . . Disponível em: https://doi.org/10.5753/jidm.2024.3368. Acesso em: 27 jun. 2024.
APA
Guimarães, G. M. C., Silva, F. X. B. da, Macêdo, L. de A. B., Lisboa, V. H. F., Marcacini, R. M., Queiroz, A. L., et al. (2024). Legal document segmentation and labeling through named entity recognition approaches. Journal of Information and Data Management - JIDM, 15( 1), 123-131. doi:10.5753/jidm.2024.3368
NLM
Guimarães GMC, Silva FXB da, Macêdo L de AB, Lisboa VHF, Marcacini RM, Queiroz AL, Borges VRP, Faleiros T de P, Garcia LPF. Legal document segmentation and labeling through named entity recognition approaches [Internet]. Journal of Information and Data Management - JIDM. 2024 ; 15( 1): 123-131.[citado 2024 jun. 27 ] Available from: https://doi.org/10.5753/jidm.2024.3368
Vancouver
Guimarães GMC, Silva FXB da, Macêdo L de AB, Lisboa VHF, Marcacini RM, Queiroz AL, Borges VRP, Faleiros T de P, Garcia LPF. Legal document segmentation and labeling through named entity recognition approaches [Internet]. Journal of Information and Data Management - JIDM. 2024 ; 15( 1): 123-131.[citado 2024 jun. 27 ] Available from: https://doi.org/10.5753/jidm.2024.3368
Artigo de periodico
Two meta-learning approaches for noise filter algorithm recommendation (2024)
Pio, Pedro Borges ; Rivolli, Adriano ; Carvalho, Andre Carlos Ponce de Leon Ferreira de ; Garcia, Luís Paulo Faina
Fonte: Journal of Information and Data Management - JIDM. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, ALGORITMOS PARA PROCESSAMENTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PIO, Pedro Borges et al. Two meta-learning approaches for noise filter algorithm recommendation. Journal of Information and Data Management - JIDM, v. 15, n. 1, p. 132-141, 2024Tradução . . Disponível em: https://doi.org/10.5753/jidm.2024.3365. Acesso em: 27 jun. 2024.
APA
Pio, P. B., Rivolli, A., Carvalho, A. C. P. de L. F. de, & Garcia, L. P. F. (2024). Two meta-learning approaches for noise filter algorithm recommendation. Journal of Information and Data Management - JIDM, 15( 1), 132-141. doi:10.5753/jidm.2024.3365
NLM
Pio PB, Rivolli A, Carvalho ACP de LF de, Garcia LPF. Two meta-learning approaches for noise filter algorithm recommendation [Internet]. Journal of Information and Data Management - JIDM. 2024 ; 15( 1): 132-141.[citado 2024 jun. 27 ] Available from: https://doi.org/10.5753/jidm.2024.3365
Vancouver
Pio PB, Rivolli A, Carvalho ACP de LF de, Garcia LPF. Two meta-learning approaches for noise filter algorithm recommendation [Internet]. Journal of Information and Data Management - JIDM. 2024 ; 15( 1): 132-141.[citado 2024 jun. 27 ] Available from: https://doi.org/10.5753/jidm.2024.3365
Artigo de periodico
Fine-tuning pre-trained neural networks for medical image classification in small clinical datasets (2024)
Spolaôr, Newton ; Lee, Huei Diana ; Mendes, Ana Isabel; Nogueira, Conceição Veloso; Parmezan, Antonio Rafael Sabino ; Takaki, Weber Shoity Resende ; Coy, Claudio Saddy Rodrigues ; Wu, Feng Chung; Fonseca-Pinto, Rui
Fonte: Multimedia Tools and Applications. Unidade: ICMC
Assuntos: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR COMPUTADOR, NEOPLASIAS CUTÂNEAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SPOLAÔR, Newton et al. Fine-tuning pre-trained neural networks for medical image classification in small clinical datasets. Multimedia Tools and Applications, v. 83, n. 9, p. 27305-27329, 2024Tradução . . Disponível em: https://doi.org/10.1007/s11042-023-16529-w. Acesso em: 27 jun. 2024.
APA
Spolaôr, N., Lee, H. D., Mendes, A. I., Nogueira, C. V., Parmezan, A. R. S., Takaki, W. S. R., et al. (2024). Fine-tuning pre-trained neural networks for medical image classification in small clinical datasets. Multimedia Tools and Applications, 83( 9), 27305-27329. doi:10.1007/s11042-023-16529-w
NLM
Spolaôr N, Lee HD, Mendes AI, Nogueira CV, Parmezan ARS, Takaki WSR, Coy CSR, Wu FC, Fonseca-Pinto R. Fine-tuning pre-trained neural networks for medical image classification in small clinical datasets [Internet]. Multimedia Tools and Applications. 2024 ; 83( 9): 27305-27329.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1007/s11042-023-16529-w
Vancouver
Spolaôr N, Lee HD, Mendes AI, Nogueira CV, Parmezan ARS, Takaki WSR, Coy CSR, Wu FC, Fonseca-Pinto R. Fine-tuning pre-trained neural networks for medical image classification in small clinical datasets [Internet]. Multimedia Tools and Applications. 2024 ; 83( 9): 27305-27329.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1007/s11042-023-16529-w
Artigo de periodico
SAnDReS 2.0: development of machine-learning models to explore the scoring function space (2024)
Azevedo, Walter Filgueira de ; Quiroga, Rodrigo ; Villarreal, Marcos Ariel; Silveira, Nelson Jose Freitas da ; Ferreira, Gabriela Bitencourt ; Silva, Amauri Duarte da ; Acosta, Martina Veit ; Oliveira, Patricia Rufino; Tutone, Marco; Biziukova, Nadezhda ; Poroikov, Vladimir ; Tarasova, Olga ; Baud, Stéphaine
Fonte: Journal of Computational Chemistry. Unidade: EACH
Assunto: APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
AZEVEDO, Walter Filgueira de et al. SAnDReS 2.0: development of machine-learning models to explore the scoring function space. Journal of Computational Chemistry, p. 01-14, 2024Tradução . . Disponível em: http://dx.doi.org/10.1002/jcc.27449. Acesso em: 27 jun. 2024.
APA
Azevedo, W. F. de, Quiroga, R., Villarreal, M. A., Silveira, N. J. F. da, Ferreira, G. B., Silva, A. D. da, et al. (2024). SAnDReS 2.0: development of machine-learning models to explore the scoring function space. Journal of Computational Chemistry, 01-14. doi:10.1002/jcc.27449
NLM
Azevedo WF de, Quiroga R, Villarreal MA, Silveira NJF da, Ferreira GB, Silva AD da, Acosta MV, Oliveira PR, Tutone M, Biziukova N, Poroikov V, Tarasova O, Baud S. SAnDReS 2.0: development of machine-learning models to explore the scoring function space [Internet]. Journal of Computational Chemistry. 2024 ; 01-14.[citado 2024 jun. 27 ] Available from: http://dx.doi.org/10.1002/jcc.27449
Vancouver
Azevedo WF de, Quiroga R, Villarreal MA, Silveira NJF da, Ferreira GB, Silva AD da, Acosta MV, Oliveira PR, Tutone M, Biziukova N, Poroikov V, Tarasova O, Baud S. SAnDReS 2.0: development of machine-learning models to explore the scoring function space [Internet]. Journal of Computational Chemistry. 2024 ; 01-14.[citado 2024 jun. 27 ] Available from: http://dx.doi.org/10.1002/jcc.27449
Artigo de periodico
Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals (2024)
Silveira, Robson Mateus Freitas ; Façanha, Débora Andréa Evangelista; McManus, Concepta; Bermejo Asensio, Luis Alberto; Silva, Iran José Oliveira da
Fonte: Computers and Electronics in Agriculture. Unidade: ESALQ
Assuntos: ADAPTAÇÃO ANIMAL, ALGORITMOS, APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL, PRODUÇÃO ANIMAL, REGULAÇÃO DA TEMPERATURA CORPORAL ANIMAL, SENSOR
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ABNT
SILVEIRA, Robson Mateus Freitas et al. Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals. Computers and Electronics in Agriculture, v. 216, p. 1-11, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2023.108502. Acesso em: 27 jun. 2024.
APA
Silveira, R. M. F., Façanha, D. A. E., McManus, C., Bermejo Asensio, L. A., & Silva, I. J. O. da. (2024). Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals. Computers and Electronics in Agriculture, 216, 1-11. doi:10.1016/j.compag.2023.108502
NLM
Silveira RMF, Façanha DAE, McManus C, Bermejo Asensio LA, Silva IJO da. Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals [Internet]. Computers and Electronics in Agriculture. 2024 ; 216 1-11.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.compag.2023.108502
Vancouver
Silveira RMF, Façanha DAE, McManus C, Bermejo Asensio LA, Silva IJO da. Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals [Internet]. Computers and Electronics in Agriculture. 2024 ; 216 1-11.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.compag.2023.108502
Artigo de periodico
Combining prompt-based language models and weak supervision for labeling named entity recognition on legal documents (2024)
Oliveira, Vitor Vasconcelos de; Nogueira, Gabriel da Silva Corvino; Faleiros, Thiago de Paulo ; Marcacini, Ricardo Marcondes
Fonte: Artificial Intelligence and Law. Unidade: ICMC
Assuntos: RECUPERAÇÃO DA INFORMAÇÃO, PROCESSAMENTO DE LINGUAGEM NATURAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Vitor Vasconcelos de et al. Combining prompt-based language models and weak supervision for labeling named entity recognition on legal documents. Artificial Intelligence and Law, 2024Tradução . . Disponível em: https://doi.org/10.1007/s10506-023-09388-1. Acesso em: 27 jun. 2024.
APA
Oliveira, V. V. de, Nogueira, G. da S. C., Faleiros, T. de P., & Marcacini, R. M. (2024). Combining prompt-based language models and weak supervision for labeling named entity recognition on legal documents. Artificial Intelligence and Law. doi:10.1007/s10506-023-09388-1
NLM
Oliveira VV de, Nogueira G da SC, Faleiros T de P, Marcacini RM. Combining prompt-based language models and weak supervision for labeling named entity recognition on legal documents [Internet]. Artificial Intelligence and Law. 2024 ;[citado 2024 jun. 27 ] Available from: https://doi.org/10.1007/s10506-023-09388-1
Vancouver
Oliveira VV de, Nogueira G da SC, Faleiros T de P, Marcacini RM. Combining prompt-based language models and weak supervision for labeling named entity recognition on legal documents [Internet]. Artificial Intelligence and Law. 2024 ;[citado 2024 jun. 27 ] Available from: https://doi.org/10.1007/s10506-023-09388-1
Artigo de periodico
Adaptive, morphometric and productive responses of Brazilian hair lambs: crossing between indigenous breeds - A machine learning approac (2024)
Silveira, Robson Mateus Freitas ; McManus, Concepta Margaret; Carrara, Eula Regina; De Vecchi, Laura Bertolaso ; Carvalho, João Rayonio de Sousa; Costa, Hélio Henrique Araújo; Pilonetto, Fabricio ; Fávero, Luiz Paulo Lopes; Landim, Aline Vieira
Fonte: Small Ruminant Research. Unidades: FEA, ESALQ, CENA
Assuntos: ADAPTAÇÃO ANIMAL, APRENDIZADO COMPUTACIONAL, CORDEIROS, CRUZAMENTO ANIMAL, MORFOMETRIA, RAÇAS ANIMAIS, REGULAÇÃO DA TEMPERATURA CORPORAL ANIMAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVEIRA, Robson Mateus Freitas et al. Adaptive, morphometric and productive responses of Brazilian hair lambs: crossing between indigenous breeds - A machine learning approac. Small Ruminant Research, v. 232, p. 1-9, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.smallrumres.2024.107208. Acesso em: 27 jun. 2024.
APA
Silveira, R. M. F., McManus, C. M., Carrara, E. R., De Vecchi, L. B., Carvalho, J. R. de S., Costa, H. H. A., et al. (2024). Adaptive, morphometric and productive responses of Brazilian hair lambs: crossing between indigenous breeds - A machine learning approac. Small Ruminant Research, 232, 1-9. doi:10.1016/j.smallrumres.2024.107208
NLM
Silveira RMF, McManus CM, Carrara ER, De Vecchi LB, Carvalho JR de S, Costa HHA, Pilonetto F, Fávero LPL, Landim AV. Adaptive, morphometric and productive responses of Brazilian hair lambs: crossing between indigenous breeds - A machine learning approac [Internet]. Small Ruminant Research. 2024 ; 232 1-9.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.smallrumres.2024.107208
Vancouver
Silveira RMF, McManus CM, Carrara ER, De Vecchi LB, Carvalho JR de S, Costa HHA, Pilonetto F, Fávero LPL, Landim AV. Adaptive, morphometric and productive responses of Brazilian hair lambs: crossing between indigenous breeds - A machine learning approac [Internet]. Small Ruminant Research. 2024 ; 232 1-9.[citado 2024 jun. 27 ] Available from: https://doi.org/10.1016/j.smallrumres.2024.107208

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