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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: 09 nov. 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 nov. 09 ] 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 nov. 09 ] Available from: https://doi.org/10.1016/j.neucom.2023.127064
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: 09 nov. 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 nov. 09 ] 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 nov. 09 ] Available from: https://doi.org/10.1016/j.compag.2024.108673
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: 09 nov. 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 nov. 09 ] 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 nov. 09 ] Available from: https://doi.org/10.1016/j.csbj.2024.05.031
Artigo de periodico
Global enhanced oil recovery assessment: A comprehensive data-driven analysis using self-organizing maps (2024)
Custódio, Luiz Felipe Niedermaier; Carneiro, Cleyton de Carvalho
Fonte: Geoenergy Science and Engineering. Unidade: EP
Assuntos: PETRÓLEO, RESERVATÓRIOS DE PETRÓLEO, APRENDIZADO COMPUTACIONAL
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CUSTÓDIO, Luiz Felipe Niedermaier e CARNEIRO, Cleyton de Carvalho. Global enhanced oil recovery assessment: A comprehensive data-driven analysis using self-organizing maps. Geoenergy Science and Engineering, v. 237, p. 212771, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.geoen.2024.21277. Acesso em: 09 nov. 2024.
APA
Custódio, L. F. N., & Carneiro, C. de C. (2024). Global enhanced oil recovery assessment: A comprehensive data-driven analysis using self-organizing maps. Geoenergy Science and Engineering, 237, 212771. doi:10.1016/j.geoen.2024.212771
NLM
Custódio LFN, Carneiro C de C. Global enhanced oil recovery assessment: A comprehensive data-driven analysis using self-organizing maps [Internet]. Geoenergy Science and Engineering. 2024 ; 237 212771.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.geoen.2024.21277
Vancouver
Custódio LFN, Carneiro C de C. Global enhanced oil recovery assessment: A comprehensive data-driven analysis using self-organizing maps [Internet]. Geoenergy Science and Engineering. 2024 ; 237 212771.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.geoen.2024.21277
Artigo de periodico
Segmenting brazilian legislative text using weak supervision and active learning (2024)
Siqueira, Felipe Alves ; Pressato, Diany ; Pereira, Fabíola Souza Fernandes ; Silva, Nádia Felix Felipe da ; Souza, Ellen Polliana Ramos ; Dias, Márcio de Souza ; Carvalho, Andre Carlos Ponce de Leon Ferreira de
Fonte: Artificial Intelligence and Law. Unidade: ICMC
Assuntos: PROCESSAMENTO DE LINGUAGEM NATURAL, TRATAMENTO AUTOMÁTICO DE TEXTOS E DISCURSOS, APRENDIZADO COMPUTACIONAL, PORTUGUÊS DO BRASIL
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SIQUEIRA, Felipe Alves et al. Segmenting brazilian legislative text using weak supervision and active learning. Artificial Intelligence and Law, 2024Tradução . . Disponível em: https://doi.org/10.1007/s10506-024-09419-5. Acesso em: 09 nov. 2024.
APA
Siqueira, F. A., Pressato, D., Pereira, F. S. F., Silva, N. F. F. da, Souza, E. P. R., Dias, M. de S., & Carvalho, A. C. P. de L. F. de. (2024). Segmenting brazilian legislative text using weak supervision and active learning. Artificial Intelligence and Law. doi:10.1007/s10506-024-09419-5
NLM
Siqueira FA, Pressato D, Pereira FSF, Silva NFF da, Souza EPR, Dias M de S, Carvalho ACP de LF de. Segmenting brazilian legislative text using weak supervision and active learning [Internet]. Artificial Intelligence and Law. 2024 ;[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s10506-024-09419-5
Vancouver
Siqueira FA, Pressato D, Pereira FSF, Silva NFF da, Souza EPR, Dias M de S, Carvalho ACP de LF de. Segmenting brazilian legislative text using weak supervision and active learning [Internet]. Artificial Intelligence and Law. 2024 ;[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s10506-024-09419-5
Artigo de periodico
Machine learning and economic forecasting: the role of international trade networks (2024)
Silva, Thiago Christiano ; Wilhelm, Paulo Victor Berri ; Amancio, Diego Raphael
Fonte: Physica A : statistical mechanics and its applications. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, REDES COMPLEXAS, COMÉRCIO INTERNACIONAL
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SILVA, Thiago Christiano e WILHELM, Paulo Victor Berri e AMANCIO, Diego Raphael. Machine learning and economic forecasting: the role of international trade networks. Physica A : statistical mechanics and its applications, v. 649, p. 1-22, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.physa.2024.129977. Acesso em: 09 nov. 2024.
APA
Silva, T. C., Wilhelm, P. V. B., & Amancio, D. R. (2024). Machine learning and economic forecasting: the role of international trade networks. Physica A : statistical mechanics and its applications, 649, 1-22. doi:10.1016/j.physa.2024.129977
NLM
Silva TC, Wilhelm PVB, Amancio DR. Machine learning and economic forecasting: the role of international trade networks [Internet]. Physica A : statistical mechanics and its applications. 2024 ; 649 1-22.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.physa.2024.129977
Vancouver
Silva TC, Wilhelm PVB, Amancio DR. Machine learning and economic forecasting: the role of international trade networks [Internet]. Physica A : statistical mechanics and its applications. 2024 ; 649 1-22.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.physa.2024.129977
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
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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: 09 nov. 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 nov. 09 ] 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 nov. 09 ] Available from: https://doi.org/10.1007/s11042-023-16529-w
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: 09 nov. 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 nov. 09 ] 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 nov. 09 ] Available from: https://doi.org/10.1016/j.compag.2024.108657
Artigo de periodico
Revealing forest structural fingerprints: An integration of LiDAR and deep learning uncovers topographical influences on Central Amazon forests (2024)
Gonçalves, Nathan Borges; Rosa, Diogo Martins; Valle, Dalton Freitas do; Smith, Marielle N; Dalagnol, Ricardo; Almeida, Danilo Roberti Alves de ; Nelson, Bruce W; Stark, Scott C
Fonte: Ecological Informatics. Unidade: ESALQ
Assuntos: APRENDIZADO COMPUTACIONAL, FLORESTAS TROPICAIS, SENSORIAMENTO REMOTO, TECNOLOGIA LIDAR, TOPOGRAFIA
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GONÇALVES, Nathan Borges et al. Revealing forest structural fingerprints: An integration of LiDAR and deep learning uncovers topographical influences on Central Amazon forests. Ecological Informatics, v. 81, p. 1-10, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.ecoinf.2024.102628. Acesso em: 09 nov. 2024.
APA
Gonçalves, N. B., Rosa, D. M., Valle, D. F. do, Smith, M. N., Dalagnol, R., Almeida, D. R. A. de, et al. (2024). Revealing forest structural fingerprints: An integration of LiDAR and deep learning uncovers topographical influences on Central Amazon forests. Ecological Informatics, 81, 1-10. doi:10.1016/j.ecoinf.2024.102628
NLM
Gonçalves NB, Rosa DM, Valle DF do, Smith MN, Dalagnol R, Almeida DRA de, Nelson BW, Stark SC. Revealing forest structural fingerprints: An integration of LiDAR and deep learning uncovers topographical influences on Central Amazon forests [Internet]. Ecological Informatics. 2024 ; 81 1-10.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.ecoinf.2024.102628
Vancouver
Gonçalves NB, Rosa DM, Valle DF do, Smith MN, Dalagnol R, Almeida DRA de, Nelson BW, Stark SC. Revealing forest structural fingerprints: An integration of LiDAR and deep learning uncovers topographical influences on Central Amazon forests [Internet]. Ecological Informatics. 2024 ; 81 1-10.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.ecoinf.2024.102628
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
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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: 09 nov. 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 nov. 09 ] 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 nov. 09 ] Available from: https://doi.org/10.1007/s10506-023-09388-1
Artigo de periodico
Accessing and modelling soil organic carbon stocks in prairies, savannas, and forests (2024)
Ruiz Potma Gonçalves, Daniel; Inagaki, Thiago Massao; Barioni, Luis Gustavo; La Scala Junior, Newton; Cherubin, Maurício Roberto ; Sá, João Carlos de Moraes; Cerri, Carlos Eduardo Pellegrino ; Anselmi, Adriano
Fonte: Catena. Unidade: ESALQ
Assuntos: APRENDIZADO COMPUTACIONAL, CARBONO, CERRADO, FLORESTAS TROPICAIS, USO DO SOLO, MATA ATLÂNTICA
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RUIZ POTMA GONÇALVES, Daniel et al. Accessing and modelling soil organic carbon stocks in prairies, savannas, and forests. Catena, v. 243, p. 1-8, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.catena.2024.108219. Acesso em: 09 nov. 2024.
APA
Ruiz Potma Gonçalves, D., Inagaki, T. M., Barioni, L. G., La Scala Junior, N., Cherubin, M. R., Sá, J. C. de M., et al. (2024). Accessing and modelling soil organic carbon stocks in prairies, savannas, and forests. Catena, 243, 1-8. doi:10.1016/j.catena.2024.108219
NLM
Ruiz Potma Gonçalves D, Inagaki TM, Barioni LG, La Scala Junior N, Cherubin MR, Sá JC de M, Cerri CEP, Anselmi A. Accessing and modelling soil organic carbon stocks in prairies, savannas, and forests [Internet]. Catena. 2024 ; 243 1-8.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.catena.2024.108219
Vancouver
Ruiz Potma Gonçalves D, Inagaki TM, Barioni LG, La Scala Junior N, Cherubin MR, Sá JC de M, Cerri CEP, Anselmi A. Accessing and modelling soil organic carbon stocks in prairies, savannas, and forests [Internet]. Catena. 2024 ; 243 1-8.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.catena.2024.108219
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: 09 nov. 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 nov. 09 ] 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 nov. 09 ] Available from: https://doi.org/10.1016/j.compag.2023.108502
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
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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: 09 nov. 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 nov. 09 ] 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 nov. 09 ] Available from: https://doi.org/10.1016/j.smallrumres.2024.107208
Artigo de periodico
Improving deep neural network random initialization through neuronal rewiring (2024)
Scabini, Leonardo Felipe dos Santos ; Baets, Bernard De ; Bruno, Odemir Martinez
Fonte: Neurocomputing. Unidade: IFSC
Assuntos: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SCABINI, Leonardo Felipe dos Santos e BAETS, Bernard De e BRUNO, Odemir Martinez. Improving deep neural network random initialization through neuronal rewiring. Neurocomputing, v. 599, p. 128130-1-128130-13 + supplementary data, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2024.128130. Acesso em: 09 nov. 2024.
APA
Scabini, L. F. dos S., Baets, B. D., & Bruno, O. M. (2024). Improving deep neural network random initialization through neuronal rewiring. Neurocomputing, 599, 128130-1-128130-13 + supplementary data. doi:10.1016/j.neucom.2024.128130
NLM
Scabini LF dos S, Baets BD, Bruno OM. Improving deep neural network random initialization through neuronal rewiring [Internet]. Neurocomputing. 2024 ; 599 128130-1-128130-13 + supplementary data.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.neucom.2024.128130
Vancouver
Scabini LF dos S, Baets BD, Bruno OM. Improving deep neural network random initialization through neuronal rewiring [Internet]. Neurocomputing. 2024 ; 599 128130-1-128130-13 + supplementary data.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.neucom.2024.128130
Artigo de periodico
From fault detection to anomaly explanation: a case study on predictive maintenance (2024)
Gama, João ; Ribeiro, Rita P ; Mastelini, Saulo Martiello ; Davari, Narjes ; Veloso, Bruno Miguel Delindro
Fonte: Web Semantics : science, services and agents on the World Wide Web. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, MANUTENÇÃO PREDITIVA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GAMA, João et al. From fault detection to anomaly explanation: a case study on predictive maintenance. Web Semantics : science, services and agents on the World Wide Web, v. 81, p. 1-9, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.websem.2024.100821. Acesso em: 09 nov. 2024.
APA
Gama, J., Ribeiro, R. P., Mastelini, S. M., Davari, N., & Veloso, B. M. D. (2024). From fault detection to anomaly explanation: a case study on predictive maintenance. Web Semantics : science, services and agents on the World Wide Web, 81, 1-9. doi:10.1016/j.websem.2024.100821
NLM
Gama J, Ribeiro RP, Mastelini SM, Davari N, Veloso BMD. From fault detection to anomaly explanation: a case study on predictive maintenance [Internet]. Web Semantics : science, services and agents on the World Wide Web. 2024 ; 81 1-9.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.websem.2024.100821
Vancouver
Gama J, Ribeiro RP, Mastelini SM, Davari N, Veloso BMD. From fault detection to anomaly explanation: a case study on predictive maintenance [Internet]. Web Semantics : science, services and agents on the World Wide Web. 2024 ; 81 1-9.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.websem.2024.100821
Artigo de periodico
Evaluation of activated sludge settling characteristics from microscopy images with deep convolutional neural networks and transfer learning (2024)
Borzooei, Sina ; Scabini, Leonardo ; Miranda, Gisele Helena Barboni ; Daneshgar, Saba ; Deblieck, Lukas; Bruno, Odemir Martinez ; Langhe, Piet De; Baets, Bernard De ; Nopens, Ingmar; Torfs, Elena
Fonte: Journal of Water Process Engineering. Unidade: IFSC
Assuntos: APRENDIZADO COMPUTACIONAL, VISÃO COMPUTACIONAL, REDES NEURAIS, TRATAMENTO DE ÁGUA
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ABNT
BORZOOEI, Sina et al. Evaluation of activated sludge settling characteristics from microscopy images with deep convolutional neural networks and transfer learning. Journal of Water Process Engineering, v. 64, p. 105692-1-105692-13, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.jwpe.2024.105692. Acesso em: 09 nov. 2024.
APA
Borzooei, S., Scabini, L., Miranda, G. H. B., Daneshgar, S., Deblieck, L., Bruno, O. M., et al. (2024). Evaluation of activated sludge settling characteristics from microscopy images with deep convolutional neural networks and transfer learning. Journal of Water Process Engineering, 64, 105692-1-105692-13. doi:10.1016/j.jwpe.2024.105692
NLM
Borzooei S, Scabini L, Miranda GHB, Daneshgar S, Deblieck L, Bruno OM, Langhe PD, Baets BD, Nopens I, Torfs E. Evaluation of activated sludge settling characteristics from microscopy images with deep convolutional neural networks and transfer learning [Internet]. Journal of Water Process Engineering. 2024 ; 64 105692-1-105692-13.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.jwpe.2024.105692
Vancouver
Borzooei S, Scabini L, Miranda GHB, Daneshgar S, Deblieck L, Bruno OM, Langhe PD, Baets BD, Nopens I, Torfs E. Evaluation of activated sludge settling characteristics from microscopy images with deep convolutional neural networks and transfer learning [Internet]. Journal of Water Process Engineering. 2024 ; 64 105692-1-105692-13.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.jwpe.2024.105692
Artigo de periodico
Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms (2024)
Mantovani, Rafael Gomes ; Horváth, Tomás ; Rossi, André Luis Debiaso ; Cerri, Ricardo ; Barbon Júnior, Sylvio ; Vanschoren, Joaquin ; Carvalho, André Carlos Ponce de Leon Ferreira de
Fonte: Data Mining and Knowledge Discovery. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, ALGORITMOS ÚTEIS E ESPECÍFICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MANTOVANI, Rafael Gomes et al. Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms. Data Mining and Knowledge Discovery, v. 38, n. 3, p. 1364-1416, 2024Tradução . . Disponível em: https://doi.org/10.1007/s10618-024-01002-5. Acesso em: 09 nov. 2024.
APA
Mantovani, R. G., Horváth, T., Rossi, A. L. D., Cerri, R., Barbon Júnior, S., Vanschoren, J., & Carvalho, A. C. P. de L. F. de. (2024). Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms. Data Mining and Knowledge Discovery, 38( 3), 1364-1416. doi:10.1007/s10618-024-01002-5
NLM
Mantovani RG, Horváth T, Rossi ALD, Cerri R, Barbon Júnior S, Vanschoren J, Carvalho ACP de LF de. Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms [Internet]. Data Mining and Knowledge Discovery. 2024 ; 38( 3): 1364-1416.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s10618-024-01002-5
Vancouver
Mantovani RG, Horváth T, Rossi ALD, Cerri R, Barbon Júnior S, Vanschoren J, Carvalho ACP de LF de. Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms [Internet]. Data Mining and Knowledge Discovery. 2024 ; 38( 3): 1364-1416.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s10618-024-01002-5
Artigo de periodico
Investigating the potential of Machine Learning for fault location on Inverter-Based Resource interconnection lines: insights and recommendations (2024)
Davi, Moisés Junior Batista Borges; Iscuissati, Rodrigo de Barros; Oleskovicz, Mario ; Lopes, Felipe V
Fonte: Electric Power Systems Research. Unidade: EESC
Assuntos: APRENDIZADO COMPUTACIONAL, FONTES RENOVÁVEIS DE ENERGIA, FALHA, ENGENHARIA ELÉTRICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DAVI, Moisés Junior Batista Borges et al. Investigating the potential of Machine Learning for fault location on Inverter-Based Resource interconnection lines: insights and recommendations. Electric Power Systems Research, v. 231, p. 1-8, 2024Tradução . . Disponível em: https://dx.doi.org/10.1016/j.epsr.2024.110366. Acesso em: 09 nov. 2024.
APA
Davi, M. J. B. B., Iscuissati, R. de B., Oleskovicz, M., & Lopes, F. V. (2024). Investigating the potential of Machine Learning for fault location on Inverter-Based Resource interconnection lines: insights and recommendations. Electric Power Systems Research, 231, 1-8. doi:10.1016/j.epsr.2024.110366
NLM
Davi MJBB, Iscuissati R de B, Oleskovicz M, Lopes FV. Investigating the potential of Machine Learning for fault location on Inverter-Based Resource interconnection lines: insights and recommendations [Internet]. Electric Power Systems Research. 2024 ; 231 1-8.[citado 2024 nov. 09 ] Available from: https://dx.doi.org/10.1016/j.epsr.2024.110366
Vancouver
Davi MJBB, Iscuissati R de B, Oleskovicz M, Lopes FV. Investigating the potential of Machine Learning for fault location on Inverter-Based Resource interconnection lines: insights and recommendations [Internet]. Electric Power Systems Research. 2024 ; 231 1-8.[citado 2024 nov. 09 ] Available from: https://dx.doi.org/10.1016/j.epsr.2024.110366
Artigo de periodico
Geotechnologies on the phosphorus stocks determination in tropical soils: general impacts on society (2024)
Rosas, Jorge Tadeu Fim ; Demattê, José Alexandre Melo ; Rosin, Nícolas Augusto ; Bartsch, Bruno dos Anjos ; Poppiel, Raul Roberto ; Rodriguez-Albarracin, Heidy Soledad ; Novais, Jean Jesus Macedo ; Pavinato, Paulo Sergio ; Ma, Yuxin; Mello, Danilo César de; Francelino, Marcio Rocha; Alves, Marcelo Rodrigo
Fonte: Science of The Total Environment. Unidade: ESALQ
Assuntos: AGRICULTURA SUSTENTÁVEL, APRENDIZADO COMPUTACIONAL, FÓSFORO, GEOPROCESSAMENTO, MAPEAMENTO DO SOLO, SENSORIAMENTO REMOTO, SOLO TROPICAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ROSAS, Jorge Tadeu Fim et al. Geotechnologies on the phosphorus stocks determination in tropical soils: general impacts on society. Science of The Total Environment, v. 938, p. 1-14, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.scitotenv.2024.173537. Acesso em: 09 nov. 2024.
APA
Rosas, J. T. F., Demattê, J. A. M., Rosin, N. A., Bartsch, B. dos A., Poppiel, R. R., Rodriguez-Albarracin, H. S., et al. (2024). Geotechnologies on the phosphorus stocks determination in tropical soils: general impacts on society. Science of The Total Environment, 938, 1-14. doi:10.1016/j.scitotenv.2024.173537
NLM
Rosas JTF, Demattê JAM, Rosin NA, Bartsch B dos A, Poppiel RR, Rodriguez-Albarracin HS, Novais JJM, Pavinato PS, Ma Y, Mello DC de, Francelino MR, Alves MR. Geotechnologies on the phosphorus stocks determination in tropical soils: general impacts on society [Internet]. Science of The Total Environment. 2024 ; 938 1-14.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.scitotenv.2024.173537
Vancouver
Rosas JTF, Demattê JAM, Rosin NA, Bartsch B dos A, Poppiel RR, Rodriguez-Albarracin HS, Novais JJM, Pavinato PS, Ma Y, Mello DC de, Francelino MR, Alves MR. Geotechnologies on the phosphorus stocks determination in tropical soils: general impacts on society [Internet]. Science of The Total Environment. 2024 ; 938 1-14.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.scitotenv.2024.173537
Artigo de periodico
Unsupervised feature based algorithms for time series extrinsic regression (2024)
Guijo-Rubio, David ; Middlehurst, Matthew ; Arcencio, Guilherme ; Silva, Diego Furtado ; Bagnall, Anthony
Fonte: Data Mining and Knowledge Discovery. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS, ALGORITMOS ÚTEIS E ESPECÍFICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GUIJO-RUBIO, David et al. Unsupervised feature based algorithms for time series extrinsic regression. Data Mining and Knowledge Discovery, v. 38, n. 4, p. 2141-2185, 2024Tradução . . Disponível em: https://doi.org/10.1007/s10618-024-01027-w. Acesso em: 09 nov. 2024.
APA
Guijo-Rubio, D., Middlehurst, M., Arcencio, G., Silva, D. F., & Bagnall, A. (2024). Unsupervised feature based algorithms for time series extrinsic regression. Data Mining and Knowledge Discovery, 38( 4), 2141-2185. doi:10.1007/s10618-024-01027-w
NLM
Guijo-Rubio D, Middlehurst M, Arcencio G, Silva DF, Bagnall A. Unsupervised feature based algorithms for time series extrinsic regression [Internet]. Data Mining and Knowledge Discovery. 2024 ; 38( 4): 2141-2185.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s10618-024-01027-w
Vancouver
Guijo-Rubio D, Middlehurst M, Arcencio G, Silva DF, Bagnall A. Unsupervised feature based algorithms for time series extrinsic regression [Internet]. Data Mining and Knowledge Discovery. 2024 ; 38( 4): 2141-2185.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s10618-024-01027-w

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