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Artigo de periodico
Solution for diagnostics of biological invasion in terrestrial ecosystems: how can deep learning help biodiversity conservation? (2026)
Ferreira, Giovanna de Andrade; Viveiros, José Matheus Segre Moneva ; Santoro, Giulio Brossi ; Amaral, Vinicius Cunha; Ferreira, Matheus Pinheiro ; Brancalion, Pedro Henrique Santin ; Molin, Paulo Guilherme
Source: Journal for Nature Conservation. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, BIODIVERSIDADE, ECOSSISTEMAS TERRESTRES, INVASÃO BIOLÓGICA, PINHEIRO, SENSORIAMENTO REMOTO
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FERREIRA, Giovanna de Andrade et al. Solution for diagnostics of biological invasion in terrestrial ecosystems: how can deep learning help biodiversity conservation?. Journal for Nature Conservation, v. 89, p. 1-10, 2026Tradução . . Disponível em: https://doi.org/10.1016/j.jnc.2025.127066. Acesso em: 08 out. 2025.
APA
Ferreira, G. de A., Viveiros, J. M. S. M., Santoro, G. B., Amaral, V. C., Ferreira, M. P., Brancalion, P. H. S., & Molin, P. G. (2026). Solution for diagnostics of biological invasion in terrestrial ecosystems: how can deep learning help biodiversity conservation? Journal for Nature Conservation, 89, 1-10. doi:10.1016/j.jnc.2025.127066
NLM
Ferreira G de A, Viveiros JMSM, Santoro GB, Amaral VC, Ferreira MP, Brancalion PHS, Molin PG. Solution for diagnostics of biological invasion in terrestrial ecosystems: how can deep learning help biodiversity conservation? [Internet]. Journal for Nature Conservation. 2026 ; 89 1-10.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.jnc.2025.127066
Vancouver
Ferreira G de A, Viveiros JMSM, Santoro GB, Amaral VC, Ferreira MP, Brancalion PHS, Molin PG. Solution for diagnostics of biological invasion in terrestrial ecosystems: how can deep learning help biodiversity conservation? [Internet]. Journal for Nature Conservation. 2026 ; 89 1-10.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.jnc.2025.127066
Artigo de periodico
High‐throughput phenotyping and machine learning techniques in soybean breeding: Exploring the potential of aerial imaging and vegetation indices (2025)
Miranda, Melissa Cristina de Carvalho ; Aono, Alexandre Hild; Fagundes, Talieisse Gomes ; Arduini, Giovanni Michelan ; Pinheiro, José Baldin
Source: Agronomy Journal. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, DOSSEL (BOTÂNICA), FENÓTIPOS, IMAGEAMENTO DE SATÉLITE, MELHORAMENTO GENÉTICO VEGETAL, SOJA
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MIRANDA, Melissa Cristina de Carvalho et al. High‐throughput phenotyping and machine learning techniques in soybean breeding: Exploring the potential of aerial imaging and vegetation indices. Agronomy Journal, v. 117, p. 1-25, 2025Tradução . . Disponível em: https://doi.org/10.1002/agj2.70012. Acesso em: 08 out. 2025.
APA
Miranda, M. C. de C., Aono, A. H., Fagundes, T. G., Arduini, G. M., & Pinheiro, J. B. (2025). High‐throughput phenotyping and machine learning techniques in soybean breeding: Exploring the potential of aerial imaging and vegetation indices. Agronomy Journal, 117, 1-25. doi:10.1002/agj2.70012
NLM
Miranda MC de C, Aono AH, Fagundes TG, Arduini GM, Pinheiro JB. High‐throughput phenotyping and machine learning techniques in soybean breeding: Exploring the potential of aerial imaging and vegetation indices [Internet]. Agronomy Journal. 2025 ; 117 1-25.[citado 2025 out. 08 ] Available from: https://doi.org/10.1002/agj2.70012
Vancouver
Miranda MC de C, Aono AH, Fagundes TG, Arduini GM, Pinheiro JB. High‐throughput phenotyping and machine learning techniques in soybean breeding: Exploring the potential of aerial imaging and vegetation indices [Internet]. Agronomy Journal. 2025 ; 117 1-25.[citado 2025 out. 08 ] Available from: https://doi.org/10.1002/agj2.70012
Artigo de periodico
Mapping soil drainage classes: comparing expert knowledge and machine learning strategies (2025)
Mello, Danilo César de ; Silvero, Nélida Elizabet Quiñonez ; Miller, Bradley A; Rosin, Nicolas Augusto ; Rosas, Jorge Tadeu Fim ; Bartsch, Bruno dos Anjos ; Veloso, Gustavo Vieira; Novais, Jean Jesus Macedo ; Falcioni, Renan; Nanni, Marcos Rafael; Alves, Marcelo Rodrigo; Fernandes-Filho, Elpídio Inácio; Santos, Uemeson José dos; Demattê, José Alexandre Melo
Source: Soil Advances. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, COR DO SOLO, DRENAGEM AGRÍCOLA, MAPEAMENTO DO SOLO, SENSORIAMENTO REMOTO
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MELLO, Danilo César de et al. Mapping soil drainage classes: comparing expert knowledge and machine learning strategies. Soil Advances, v. 3, p. 1-11, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.soilad.2024.100028. Acesso em: 08 out. 2025.
APA
Mello, D. C. de, Silvero, N. E. Q., Miller, B. A., Rosin, N. A., Rosas, J. T. F., Bartsch, B. dos A., et al. (2025). Mapping soil drainage classes: comparing expert knowledge and machine learning strategies. Soil Advances, 3, 1-11. doi:10.1016/j.soilad.2024.100028
NLM
Mello DC de, Silvero NEQ, Miller BA, Rosin NA, Rosas JTF, Bartsch B dos A, Veloso GV, Novais JJM, Falcioni R, Nanni MR, Alves MR, Fernandes-Filho EI, Santos UJ dos, Demattê JAM. Mapping soil drainage classes: comparing expert knowledge and machine learning strategies [Internet]. Soil Advances. 2025 ; 3 1-11.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.soilad.2024.100028
Vancouver
Mello DC de, Silvero NEQ, Miller BA, Rosin NA, Rosas JTF, Bartsch B dos A, Veloso GV, Novais JJM, Falcioni R, Nanni MR, Alves MR, Fernandes-Filho EI, Santos UJ dos, Demattê JAM. Mapping soil drainage classes: comparing expert knowledge and machine learning strategies [Internet]. Soil Advances. 2025 ; 3 1-11.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.soilad.2024.100028
Trabalho de evento-anais periodico
Growing self-organizing maps for multi-label classification (2025)
Casarotto, Pedro Henrique; Cerri, Ricardo
Source: Lecture Notes in Artificial Intelligence. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS
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CASAROTTO, Pedro Henrique e CERRI, Ricardo. Growing self-organizing maps for multi-label classification. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-79032-4_3. Acesso em: 08 out. 2025. , 2025
APA
Casarotto, P. H., & Cerri, R. (2025). Growing self-organizing maps for multi-label classification. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-79032-4_3
NLM
Casarotto PH, Cerri R. Growing self-organizing maps for multi-label classification [Internet]. Lecture Notes in Artificial Intelligence. 2025 ; 15413 33-48.[citado 2025 out. 08 ] Available from: https://doi.org/10.1007/978-3-031-79032-4_3
Vancouver
Casarotto PH, Cerri R. Growing self-organizing maps for multi-label classification [Internet]. Lecture Notes in Artificial Intelligence. 2025 ; 15413 33-48.[citado 2025 out. 08 ] Available from: https://doi.org/10.1007/978-3-031-79032-4_3
Artigo de periodico
A study of transductive graph-based regression (2025)
Nespolo, Renan Guilherme ; Valejo, Alan Demetrius Baria ; Lopes, Alneu de Andrade
Source: International Journal of Computer Information Systems and Industrial Management Applications. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, TEORIA DOS GRAFOS, REGRESSÃO LINEAR
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NESPOLO, Renan Guilherme e VALEJO, Alan Demetrius Baria e LOPES, Alneu de Andrade. A study of transductive graph-based regression. International Journal of Computer Information Systems and Industrial Management Applications, v. 17, p. 99-116, 2025Tradução . . Disponível em: https://doi.org/10.70917/2025008. Acesso em: 08 out. 2025.
APA
Nespolo, R. G., Valejo, A. D. B., & Lopes, A. de A. (2025). A study of transductive graph-based regression. International Journal of Computer Information Systems and Industrial Management Applications, 17, 99-116. doi:10.70917/2025008
NLM
Nespolo RG, Valejo ADB, Lopes A de A. A study of transductive graph-based regression [Internet]. International Journal of Computer Information Systems and Industrial Management Applications. 2025 ; 17 99-116.[citado 2025 out. 08 ] Available from: https://doi.org/10.70917/2025008
Vancouver
Nespolo RG, Valejo ADB, Lopes A de A. A study of transductive graph-based regression [Internet]. International Journal of Computer Information Systems and Industrial Management Applications. 2025 ; 17 99-116.[citado 2025 out. 08 ] Available from: https://doi.org/10.70917/2025008
Trabalho de evento-anais periodico
Semi-supervised predictive clustering trees for multi-label protein subcellular localization (2025)
Alcantara, Leonardo Utida; Triguero, Isaac ; Cerri, Ricardo
Source: Lecture Notes in Artificial Intelligence. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Subjects: BIOINFORMÁTICA, APRENDIZADO COMPUTACIONAL
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ALCANTARA, Leonardo Utida e TRIGUERO, Isaac e CERRI, Ricardo. Semi-supervised predictive clustering trees for multi-label protein subcellular localization. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-79032-4_27. Acesso em: 08 out. 2025. , 2025
APA
Alcantara, L. U., Triguero, I., & Cerri, R. (2025). Semi-supervised predictive clustering trees for multi-label protein subcellular localization. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-79032-4_27
NLM
Alcantara LU, Triguero I, Cerri R. Semi-supervised predictive clustering trees for multi-label protein subcellular localization [Internet]. Lecture Notes in Artificial Intelligence. 2025 ; 15413 384-399.[citado 2025 out. 08 ] Available from: https://doi.org/10.1007/978-3-031-79032-4_27
Vancouver
Alcantara LU, Triguero I, Cerri R. Semi-supervised predictive clustering trees for multi-label protein subcellular localization [Internet]. Lecture Notes in Artificial Intelligence. 2025 ; 15413 384-399.[citado 2025 out. 08 ] Available from: https://doi.org/10.1007/978-3-031-79032-4_27
Artigo de periodico
Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change (2025)
Silveira, Robson Mateus Freitas ; Vasconcelos, Angela Maria de; McManus, Concepta ; Fávero, Luiz Paulo Lopes; Silva, Iran José Oliveira da
Source: Smart Agricultural Technology. Unidades: FEA, ESALQ, CENA
Subjects: ADAPTAÇÃO ANIMAL, APRENDIZADO COMPUTACIONAL, COMPOSIÇÃO DE ALIMENTOS, FENÓTIPOS, HORMÔNIOS TIREOIDIANOS, LEITE, MUDANÇA CLIMÁTICA, VACAS
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SILVEIRA, Robson Mateus Freitas et al. Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change. Smart Agricultural Technology, v. 12, p. 1-14, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.atech.2025.101128. Acesso em: 08 out. 2025.
APA
Silveira, R. M. F., Vasconcelos, A. M. de, McManus, C., Fávero, L. P. L., & Silva, I. J. O. da. (2025). Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change. Smart Agricultural Technology, 12, 1-14. doi:10.1016/j.atech.2025.101128
NLM
Silveira RMF, Vasconcelos AM de, McManus C, Fávero LPL, Silva IJO da. Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change [Internet]. Smart Agricultural Technology. 2025 ; 12 1-14.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.atech.2025.101128
Vancouver
Silveira RMF, Vasconcelos AM de, McManus C, Fávero LPL, Silva IJO da. Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change [Internet]. Smart Agricultural Technology. 2025 ; 12 1-14.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.atech.2025.101128
Artigo de periodico
Mapping clay fraction oxides in Brazil using Earth observation strategy (2025)
Rosas, Jorge Tadeu Fim ; Demattê, José Alexandre Melo ; Rosin, Nícolas Augusto ; Poppiel, Raul Roberto ; Silvero, Nélida Elizabet Quiñonez ; Amorim, Merilyn Taynara Accorsi ; Rodríguez-Albarracín, Heidy Soledad ; Vogel, Letícia Guadagnin ; Bartsch, Bruno dos Anjos ; Souza, José João Lelis Leal de; Gomes, Lucas de Carvalho; Mello, Danilo César de
Source: Geoderma. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, ARGILAS, IMAGEAMENTO DE SATÉLITE, INTEMPERISMO, MAPEAMENTO DO SOLO, SERVIÇOS AMBIENTAIS
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ROSAS, Jorge Tadeu Fim et al. Mapping clay fraction oxides in Brazil using Earth observation strategy. Geoderma, v. 460, p. 1-17, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.geoderma.2025.117425. Acesso em: 08 out. 2025.
APA
Rosas, J. T. F., Demattê, J. A. M., Rosin, N. A., Poppiel, R. R., Silvero, N. E. Q., Amorim, M. T. A., et al. (2025). Mapping clay fraction oxides in Brazil using Earth observation strategy. Geoderma, 460, 1-17. doi:10.1016/j.geoderma.2025.117425
NLM
Rosas JTF, Demattê JAM, Rosin NA, Poppiel RR, Silvero NEQ, Amorim MTA, Rodríguez-Albarracín HS, Vogel LG, Bartsch B dos A, Souza JJLL de, Gomes L de C, Mello DC de. Mapping clay fraction oxides in Brazil using Earth observation strategy [Internet]. Geoderma. 2025 ; 460 1-17.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.geoderma.2025.117425
Vancouver
Rosas JTF, Demattê JAM, Rosin NA, Poppiel RR, Silvero NEQ, Amorim MTA, Rodríguez-Albarracín HS, Vogel LG, Bartsch B dos A, Souza JJLL de, Gomes L de C, Mello DC de. Mapping clay fraction oxides in Brazil using Earth observation strategy [Internet]. Geoderma. 2025 ; 460 1-17.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.geoderma.2025.117425
Artigo de periodico
Parameter inference in nonlinear dynamical systems via recurrence plots and convolutional neural networks (2025)
Lober, Luiza ; Palmero, Matheus ; Rodrigues, Francisco Aparecido
Source: Physical Review E. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES COMPLEXAS
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ABNT
LOBER, Luiza e PALMERO, Matheus e RODRIGUES, Francisco Aparecido. Parameter inference in nonlinear dynamical systems via recurrence plots and convolutional neural networks. Physical Review E, v. 112, p. 014210-1-014210-13, 2025Tradução . . Disponível em: https://doi.org/10.1103/wz7j-lzvs. Acesso em: 08 out. 2025.
APA
Lober, L., Palmero, M., & Rodrigues, F. A. (2025). Parameter inference in nonlinear dynamical systems via recurrence plots and convolutional neural networks. Physical Review E, 112, 014210-1-014210-13. doi:10.1103/wz7j-lzvs
NLM
Lober L, Palmero M, Rodrigues FA. Parameter inference in nonlinear dynamical systems via recurrence plots and convolutional neural networks [Internet]. Physical Review E. 2025 ; 112 014210-1-014210-13.[citado 2025 out. 08 ] Available from: https://doi.org/10.1103/wz7j-lzvs
Vancouver
Lober L, Palmero M, Rodrigues FA. Parameter inference in nonlinear dynamical systems via recurrence plots and convolutional neural networks [Internet]. Physical Review E. 2025 ; 112 014210-1-014210-13.[citado 2025 out. 08 ] Available from: https://doi.org/10.1103/wz7j-lzvs
Tese (Doutorado)
Anomaly Detection and Root Cause Analysis in Cloud-Native Environments Using Large Language Models and Bayesian Networks (2025)
Pedroso, Diego Frazatto ; Bruschi, Sarita Mazzini (Orientador)
Unidade: ICMC
Subjects: COMPUTAÇÃO EM NUVEM, CONFIABILIDADE DE SOFTWARE, APRENDIZADO COMPUTACIONAL, TECNOLOGIA DA INFORMAÇÃO
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PEDROSO, Diego Frazatto. Anomaly Detection and Root Cause Analysis in Cloud-Native Environments Using Large Language Models and Bayesian Networks. 2025. Tese (Doutorado) – Universidade de São Paulo, São Carlos, 2025. Disponível em: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-27082025-141523/. Acesso em: 08 out. 2025.
APA
Pedroso, D. F. (2025). Anomaly Detection and Root Cause Analysis in Cloud-Native Environments Using Large Language Models and Bayesian Networks (Tese (Doutorado). Universidade de São Paulo, São Carlos. Recuperado de https://www.teses.usp.br/teses/disponiveis/55/55134/tde-27082025-141523/
NLM
Pedroso DF. Anomaly Detection and Root Cause Analysis in Cloud-Native Environments Using Large Language Models and Bayesian Networks [Internet]. 2025 ;[citado 2025 out. 08 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-27082025-141523/
Vancouver
Pedroso DF. Anomaly Detection and Root Cause Analysis in Cloud-Native Environments Using Large Language Models and Bayesian Networks [Internet]. 2025 ;[citado 2025 out. 08 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-27082025-141523/
Artigo de periodico
Frontiers in earth observation for global soil properties assessment linked to environmental and socio-economic factors (2025)
Demattê, José Alexandre Melo ; Poppiel, Raúl Roberto ; Novais, Jean de Jesus Macedo ; Rosin, Nícolas Augusto ; Minasny, Budiman ; Savin, Igor Y; Grunwald, Sabine ; Chen, Songchao ; Hong, Yongsheng; De Jong Van Lier, Quirijn
Source: The Innovation. Unidades: ESALQ, CENA
Subjects: APRENDIZADO COMPUTACIONAL, MAPEAMENTO DO SOLO, SENSORIAMENTO REMOTO, SEQUESTRO DE CARBONO, SOLOS
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DEMATTÊ, José Alexandre Melo et al. Frontiers in earth observation for global soil properties assessment linked to environmental and socio-economic factors. The Innovation, v. 6, n. 9, p. 1-13, 2025Tradução . . Disponível em: https://www.sciencedirect.com/science/article/pii/S2666675825001882?via%3Dihub. Acesso em: 08 out. 2025.
APA
Demattê, J. A. M., Poppiel, R. R., Novais, J. de J. M., Rosin, N. A., Minasny, B., Savin, I. Y., et al. (2025). Frontiers in earth observation for global soil properties assessment linked to environmental and socio-economic factors. The Innovation, 6( 9), 1-13. doi:10.1016/j.xinn.2025.100985
NLM
Demattê JAM, Poppiel RR, Novais J de JM, Rosin NA, Minasny B, Savin IY, Grunwald S, Chen S, Hong Y, De Jong Van Lier Q. Frontiers in earth observation for global soil properties assessment linked to environmental and socio-economic factors [Internet]. The Innovation. 2025 ; 6( 9): 1-13.[citado 2025 out. 08 ] Available from: https://www.sciencedirect.com/science/article/pii/S2666675825001882?via%3Dihub
Vancouver
Demattê JAM, Poppiel RR, Novais J de JM, Rosin NA, Minasny B, Savin IY, Grunwald S, Chen S, Hong Y, De Jong Van Lier Q. Frontiers in earth observation for global soil properties assessment linked to environmental and socio-economic factors [Internet]. The Innovation. 2025 ; 6( 9): 1-13.[citado 2025 out. 08 ] Available from: https://www.sciencedirect.com/science/article/pii/S2666675825001882?via%3Dihub
Trabalho de evento
LLM4Gov: a privacy-preserving approach to teacher-student fine-tuning of distilled LLMs for the public sector (2025)
Marcacini, Ricardo Marcondes ; Valverde-Rebaza, Jorge Carlos ; Turine, Marcelo Augusto Santos ; Santos, Brucce Neves dos ; Levcovitz, Silvio; Rezende, Solange Oliveira
Source: Anais. Conference titles: Congresso da Sociedade Brasileira de Computação - CSBC. Unidade: ICMC
Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL, APRENDIZADO COMPUTACIONAL, GOVERNO ELETRÔNICO, PROTEÇÃO DE DADOS PESSOAIS
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MARCACINI, Ricardo Marcondes et al. LLM4Gov: a privacy-preserving approach to teacher-student fine-tuning of distilled LLMs for the public sector. 2025, Anais.. Porto Alegre: SBC, 2025. Disponível em: https://doi.org/10.5753/lasdigov.2025.9471. Acesso em: 08 out. 2025.
APA
Marcacini, R. M., Valverde-Rebaza, J. C., Turine, M. A. S., Santos, B. N. dos, Levcovitz, S., & Rezende, S. O. (2025). LLM4Gov: a privacy-preserving approach to teacher-student fine-tuning of distilled LLMs for the public sector. In Anais. Porto Alegre: SBC. doi:10.5753/lasdigov.2025.9471
NLM
Marcacini RM, Valverde-Rebaza JC, Turine MAS, Santos BN dos, Levcovitz S, Rezende SO. LLM4Gov: a privacy-preserving approach to teacher-student fine-tuning of distilled LLMs for the public sector [Internet]. Anais. 2025 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.5753/lasdigov.2025.9471
Vancouver
Marcacini RM, Valverde-Rebaza JC, Turine MAS, Santos BN dos, Levcovitz S, Rezende SO. LLM4Gov: a privacy-preserving approach to teacher-student fine-tuning of distilled LLMs for the public sector [Internet]. Anais. 2025 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.5753/lasdigov.2025.9471
Dissertação (Mestrado)
Sensoriamento orbital e machine learning para mapeamento e estimativa de estoque de carbono de Organossolos sob floresta no Vale do Ribeira (SP) (2025)
Silva, Bruno Ferreira da ; Torrado, Pablo Vidal (Orientador)
Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, CARBONO, MAPEAMENTO DO SOLO, ORGANOSSOLOS, SENSORIAMENTO REMOTO, SOLO FLORESTAL
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ABNT
SILVA, Bruno Ferreira da. Sensoriamento orbital e machine learning para mapeamento e estimativa de estoque de carbono de Organossolos sob floresta no Vale do Ribeira (SP). 2025. Dissertação (Mestrado) – Universidade de São Paulo, Piracicaba, 2025. Disponível em: https://www.teses.usp.br/teses/disponiveis/11/11140/tde-02102025-180046/. Acesso em: 08 out. 2025.
APA
Silva, B. F. da. (2025). Sensoriamento orbital e machine learning para mapeamento e estimativa de estoque de carbono de Organossolos sob floresta no Vale do Ribeira (SP) (Dissertação (Mestrado). Universidade de São Paulo, Piracicaba. Recuperado de https://www.teses.usp.br/teses/disponiveis/11/11140/tde-02102025-180046/
NLM
Silva BF da. Sensoriamento orbital e machine learning para mapeamento e estimativa de estoque de carbono de Organossolos sob floresta no Vale do Ribeira (SP) [Internet]. 2025 ;[citado 2025 out. 08 ] Available from: https://www.teses.usp.br/teses/disponiveis/11/11140/tde-02102025-180046/
Vancouver
Silva BF da. Sensoriamento orbital e machine learning para mapeamento e estimativa de estoque de carbono de Organossolos sob floresta no Vale do Ribeira (SP) [Internet]. 2025 ;[citado 2025 out. 08 ] Available from: https://www.teses.usp.br/teses/disponiveis/11/11140/tde-02102025-180046/
Artigo de periodico
Using machine learning and optical microscopy image analysis of immunosensors made on plasmonic substrates: application to detect the SARS-CoV-2 virus (2025)
Oiticica, Pedro Ramon Almeida ; Angelim, Monara Kaélle Servulo Cruz ; Soares, Juliana Coatrini ; Soares, Andrey Coatrini ; Proença-Modena, José Luiz ; Bruno, Odemir Martinez ; Oliveira Junior, Osvaldo Novais de
Source: ACS Sensors. Unidade: IFSC
Subjects: MICROSCÓPIO ÓTICO, APRENDIZADO COMPUTACIONAL, COVID-19, VISÃO COMPUTACIONAL
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OITICICA, Pedro Ramon Almeida et al. Using machine learning and optical microscopy image analysis of immunosensors made on plasmonic substrates: application to detect the SARS-CoV-2 virus. ACS Sensors, v. 10, n. 2, p. 1407-1418 + supporting information, 2025Tradução . . Disponível em: https://doi.org/10.1021/acssensors.4c03451. Acesso em: 08 out. 2025.
APA
Oiticica, P. R. A., Angelim, M. K. S. C., Soares, J. C., Soares, A. C., Proença-Modena, J. L., Bruno, O. M., & Oliveira Junior, O. N. de. (2025). Using machine learning and optical microscopy image analysis of immunosensors made on plasmonic substrates: application to detect the SARS-CoV-2 virus. ACS Sensors, 10( 2), 1407-1418 + supporting information. doi:10.1021/acssensors.4c03451
NLM
Oiticica PRA, Angelim MKSC, Soares JC, Soares AC, Proença-Modena JL, Bruno OM, Oliveira Junior ON de. Using machine learning and optical microscopy image analysis of immunosensors made on plasmonic substrates: application to detect the SARS-CoV-2 virus [Internet]. ACS Sensors. 2025 ; 10( 2): 1407-1418 + supporting information.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acssensors.4c03451
Vancouver
Oiticica PRA, Angelim MKSC, Soares JC, Soares AC, Proença-Modena JL, Bruno OM, Oliveira Junior ON de. Using machine learning and optical microscopy image analysis of immunosensors made on plasmonic substrates: application to detect the SARS-CoV-2 virus [Internet]. ACS Sensors. 2025 ; 10( 2): 1407-1418 + supporting information.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acssensors.4c03451
Artigo de periodico
Adding imprecision to hypotheses: a Bayesian framework for testing practical significance in nonparametric settings (2025)
Lassance, Rodrigo Ferrari Lucas; Izbicki, Rafael ; Stern, Rafael Bassi
Source: International Journal of Approximate Reasoning. Unidade: IME
Subjects: INFERÊNCIA BAYESIANA, INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LASSANCE, Rodrigo Ferrari Lucas e IZBICKI, Rafael e STERN, Rafael Bassi. Adding imprecision to hypotheses: a Bayesian framework for testing practical significance in nonparametric settings. International Journal of Approximate Reasoning, v. 178, n. artigo 109332, p. 1-25, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2024.109332. Acesso em: 08 out. 2025.
APA
Lassance, R. F. L., Izbicki, R., & Stern, R. B. (2025). Adding imprecision to hypotheses: a Bayesian framework for testing practical significance in nonparametric settings. International Journal of Approximate Reasoning, 178( artigo 109332), 1-25. doi:10.1016/j.ijar.2024.109332
NLM
Lassance RFL, Izbicki R, Stern RB. Adding imprecision to hypotheses: a Bayesian framework for testing practical significance in nonparametric settings [Internet]. International Journal of Approximate Reasoning. 2025 ; 178( artigo 109332): 1-25.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.ijar.2024.109332
Vancouver
Lassance RFL, Izbicki R, Stern RB. Adding imprecision to hypotheses: a Bayesian framework for testing practical significance in nonparametric settings [Internet]. International Journal of Approximate Reasoning. 2025 ; 178( artigo 109332): 1-25.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.ijar.2024.109332
Artigo de periodico
Cryogenic turning of Ti-15Mo alloy (2025)
Cardenas Rubio, Juan Camilo; Ricci, Virgilio Pereira; Rodrigues, Alessandro Roger ; Kliauga, Andrea Madeira ; Ventura, Carlos Eiji Hirata
Source: International Journal of Advanced Manufacturing Technology. Unidade: EESC
Subjects: APRENDIZADO COMPUTACIONAL, ACIDENTE VASCULAR CEREBRAL, REGRESSÃO LOGÍSTICA, ENGENHARIA MECÂNICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CARDENAS RUBIO, Juan Camilo et al. Cryogenic turning of Ti-15Mo alloy. International Journal of Advanced Manufacturing Technology, v. 137, p. 4129-4141, 2025Tradução . . Disponível em: http://dx.doi.org/10.1007/s00170-025-15410-4. Acesso em: 08 out. 2025.
APA
Cardenas Rubio, J. C., Ricci, V. P., Rodrigues, A. R., Kliauga, A. M., & Ventura, C. E. H. (2025). Cryogenic turning of Ti-15Mo alloy. International Journal of Advanced Manufacturing Technology, 137, 4129-4141. doi:10.1007/s00170-025-15410-4
NLM
Cardenas Rubio JC, Ricci VP, Rodrigues AR, Kliauga AM, Ventura CEH. Cryogenic turning of Ti-15Mo alloy [Internet]. International Journal of Advanced Manufacturing Technology. 2025 ; 137 4129-4141.[citado 2025 out. 08 ] Available from: http://dx.doi.org/10.1007/s00170-025-15410-4
Vancouver
Cardenas Rubio JC, Ricci VP, Rodrigues AR, Kliauga AM, Ventura CEH. Cryogenic turning of Ti-15Mo alloy [Internet]. International Journal of Advanced Manufacturing Technology. 2025 ; 137 4129-4141.[citado 2025 out. 08 ] Available from: http://dx.doi.org/10.1007/s00170-025-15410-4
Artigo de periodico
A comparative survey of vision transformers for feature extraction in texture analysis (2025)
Scabini, Leonardo Felipe dos Santos ; Sacilotti, Andre ; Zielinski, Kallil Miguel Caparroz ; Ribas, Lucas Correia ; De Baets, Bernard ; Bruno, Odemir Martinez
Source: Journal of Imaging. Unidades: IFSC, ICMC
Subjects: VISÃO COMPUTACIONAL, 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 et al. A comparative survey of vision transformers for feature extraction in texture analysis. Journal of Imaging, v. 11, n. 9, p. 304-1-304-26, 2025Tradução . . Disponível em: https://doi.org/10.3390/jimaging11090304. Acesso em: 08 out. 2025.
APA
Scabini, L. F. dos S., Sacilotti, A., Zielinski, K. M. C., Ribas, L. C., De Baets, B., & Bruno, O. M. (2025). A comparative survey of vision transformers for feature extraction in texture analysis. Journal of Imaging, 11( 9), 304-1-304-26. doi:10.3390/jimaging11090304
NLM
Scabini LF dos S, Sacilotti A, Zielinski KMC, Ribas LC, De Baets B, Bruno OM. A comparative survey of vision transformers for feature extraction in texture analysis [Internet]. Journal of Imaging. 2025 ; 11( 9): 304-1-304-26.[citado 2025 out. 08 ] Available from: https://doi.org/10.3390/jimaging11090304
Vancouver
Scabini LF dos S, Sacilotti A, Zielinski KMC, Ribas LC, De Baets B, Bruno OM. A comparative survey of vision transformers for feature extraction in texture analysis [Internet]. Journal of Imaging. 2025 ; 11( 9): 304-1-304-26.[citado 2025 out. 08 ] Available from: https://doi.org/10.3390/jimaging11090304
Trabalho de evento
Not only what, but also when: understanding brazilian political comments on legislative bills over time through stance detection and topic modeling (2025)
Pinto, Matheus Henrique de Cerqueira ; Silva, Nádia Felix Felipe da ; Souza, Ellen Polliana Ramos ; Albuquerque, Hidelberg Oliveira ; Dias, Márcio de Souza ; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Proceedings. Conference titles: Annual International Conference on Digital Government Research - DG.O. Unidade: ICMC
Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL, RECONHECIMENTO DE TEXTO, APRENDIZADO COMPUTACIONAL, PORTUGUÊS DO BRASIL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PINTO, Matheus Henrique de Cerqueira et al. Not only what, but also when: understanding brazilian political comments on legislative bills over time through stance detection and topic modeling. 2025, Anais.. [S.l.]: Digital Government Society - DGS, 2025. Disponível em: https://doi.org/10.59490/dgo.2025.955. Acesso em: 08 out. 2025.
APA
Pinto, M. H. de C., Silva, N. F. F. da, Souza, E. P. R., Albuquerque, H. O., Dias, M. de S., & Carvalho, A. C. P. de L. F. de. (2025). Not only what, but also when: understanding brazilian political comments on legislative bills over time through stance detection and topic modeling. In Proceedings. [S.l.]: Digital Government Society - DGS. doi:10.59490/dgo.2025.955
NLM
Pinto MH de C, Silva NFF da, Souza EPR, Albuquerque HO, Dias M de S, Carvalho ACP de LF de. Not only what, but also when: understanding brazilian political comments on legislative bills over time through stance detection and topic modeling [Internet]. Proceedings. 2025 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.59490/dgo.2025.955
Vancouver
Pinto MH de C, Silva NFF da, Souza EPR, Albuquerque HO, Dias M de S, Carvalho ACP de LF de. Not only what, but also when: understanding brazilian political comments on legislative bills over time through stance detection and topic modeling [Internet]. Proceedings. 2025 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.59490/dgo.2025.955
Artigo de periodico
A new dataset for measuring the performance of blood vessel segmentation methods under distribution shifts (2025)
Silva, Matheus Viana da ; Santos, Natália de Carvalho ; Ouellette, Julie; Lacoste, Baptiste ; Comin, Cesar Henrique
Source: PLoS One. Unidade: IFSC
Subjects: APRENDIZADO COMPUTACIONAL, MICROSCOPIA DE FLUORESCÊNCIA, REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVA, Matheus Viana da et al. A new dataset for measuring the performance of blood vessel segmentation methods under distribution shifts. PLoS One, v. 20, n. 5, p. e0322048-1-e0322048-25 + supporting material, 2025Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0322048. Acesso em: 08 out. 2025.
APA
Silva, M. V. da, Santos, N. de C., Ouellette, J., Lacoste, B., & Comin, C. H. (2025). A new dataset for measuring the performance of blood vessel segmentation methods under distribution shifts. PLoS One, 20( 5), e0322048-1-e0322048-25 + supporting material. doi:10.1371/journal.pone.0322048
NLM
Silva MV da, Santos N de C, Ouellette J, Lacoste B, Comin CH. A new dataset for measuring the performance of blood vessel segmentation methods under distribution shifts [Internet]. PLoS One. 2025 ; 20( 5): e0322048-1-e0322048-25 + supporting material.[citado 2025 out. 08 ] Available from: https://doi.org/10.1371/journal.pone.0322048
Vancouver
Silva MV da, Santos N de C, Ouellette J, Lacoste B, Comin CH. A new dataset for measuring the performance of blood vessel segmentation methods under distribution shifts [Internet]. PLoS One. 2025 ; 20( 5): e0322048-1-e0322048-25 + supporting material.[citado 2025 out. 08 ] Available from: https://doi.org/10.1371/journal.pone.0322048
Artigo de periodico
Advances in application of federated machine learning for oncology and cancer diagnosis (2025)
Nasajpour, Mohammad ; Pouriyeh, Seyedamin ; Parizi, Reza M ; Han, Meng ; Mosaiyebzadeh, Fatemeh ; Xie, Yixin ; Liu, Liyuan ; Batista, Daniel Macêdo
Source: Information. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, DIAGNÓSTICO, ONCOLOGIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NASAJPOUR, Mohammad et al. Advances in application of federated machine learning for oncology and cancer diagnosis. Information, v. 16, n. artigo 487, p. 1-31, 2025Tradução . . Disponível em: https://doi.org/10.3390/info16060487. Acesso em: 08 out. 2025.
APA
Nasajpour, M., Pouriyeh, S., Parizi, R. M., Han, M., Mosaiyebzadeh, F., Xie, Y., et al. (2025). Advances in application of federated machine learning for oncology and cancer diagnosis. Information, 16( artigo 487), 1-31. doi:10.3390/info16060487
NLM
Nasajpour M, Pouriyeh S, Parizi RM, Han M, Mosaiyebzadeh F, Xie Y, Liu L, Batista DM. Advances in application of federated machine learning for oncology and cancer diagnosis [Internet]. Information. 2025 ; 16( artigo 487): 1-31.[citado 2025 out. 08 ] Available from: https://doi.org/10.3390/info16060487
Vancouver
Nasajpour M, Pouriyeh S, Parizi RM, Han M, Mosaiyebzadeh F, Xie Y, Liu L, Batista DM. Advances in application of federated machine learning for oncology and cancer diagnosis [Internet]. Information. 2025 ; 16( artigo 487): 1-31.[citado 2025 out. 08 ] Available from: https://doi.org/10.3390/info16060487

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