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Trabalho de evento-anais periodico
DIF-SR: a differential item functioning-based sample reweighting method (2024)
Minatel, Diego ; Parmezan, Antonio Rafael Sabino ; Cúri, Mariana ; Lopes, Alneu de Andrade
Fonte: Lecture Notes in Computer Science. Nome do evento: Iberoamerican Congress on Pattern Recognition - CIARP. Unidade: ICMC
Assuntos: TEORIA DE RESPOSTA AO ITEM, APRENDIZADO COMPUTACIONAL
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ABNT
MINATEL, Diego et al. DIF-SR: a differential item functioning-based sample reweighting method. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-49018-7_45. Acesso em: 19 nov. 2025. , 2024
APA
Minatel, D., Parmezan, A. R. S., Cúri, M., & Lopes, A. de A. (2024). DIF-SR: a differential item functioning-based sample reweighting method. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-031-49018-7_45
NLM
Minatel D, Parmezan ARS, Cúri M, Lopes A de A. DIF-SR: a differential item functioning-based sample reweighting method [Internet]. Lecture Notes in Computer Science. 2024 ; 14469 630-645.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1007/978-3-031-49018-7_45
Vancouver
Minatel D, Parmezan ARS, Cúri M, Lopes A de A. DIF-SR: a differential item functioning-based sample reweighting method [Internet]. Lecture Notes in Computer Science. 2024 ; 14469 630-645.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1007/978-3-031-49018-7_45
Trabalho de evento-anais periodico
Bipartite graph coarsening for text classification using graph neural networks (2024)
Santos, Nícolas Roque dos ; Minatel, Diego ; Valejo, Alan Demetrius Baria ; Lopes, Alneu de Andrade
Fonte: Lecture Notes in Computer Science. Nome do evento: Iberoamerican Congress on Pattern Recognition - CIARP. Unidade: ICMC
Assuntos: MINERAÇÃO DE DADOS, REDES NEURAIS
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ABNT
SANTOS, Nícolas Roque dos et al. Bipartite graph coarsening for text classification using graph neural networks. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-49018-7_42. Acesso em: 19 nov. 2025. , 2024
APA
Santos, N. R. dos, Minatel, D., Valejo, A. D. B., & Lopes, A. de A. (2024). Bipartite graph coarsening for text classification using graph neural networks. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-031-49018-7_42
NLM
Santos NR dos, Minatel D, Valejo ADB, Lopes A de A. Bipartite graph coarsening for text classification using graph neural networks [Internet]. Lecture Notes in Computer Science. 2024 ; 14469 589-604.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1007/978-3-031-49018-7_42
Vancouver
Santos NR dos, Minatel D, Valejo ADB, Lopes A de A. Bipartite graph coarsening for text classification using graph neural networks [Internet]. Lecture Notes in Computer Science. 2024 ; 14469 589-604.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1007/978-3-031-49018-7_42
Trabalho de evento-anais periodico
Enhancing explainability in oral cancer detection with Grad-CAM visualizations (2024)
Silva, Arnaldo Vitor Barros da ; Saldivia-Siracusa, Cristina ; Souza, Eduardo Santos Carlos de ; Araujo, Anna Luiza Damaceno ; Lopes, Márcio Ajudarte ; Vargas, Pablo Agustin ; Kowalski, Luiz Paulo ; Santos-Silva, Alan Roger dos ; Carvalho, Andre Carlos Ponce de Leon Ferreira de ; Quiles, Marcos Gonçalves
Fonte: Lecture Notes in Computer Science. Nome do evento: International Conference on Computational Science and its Applications - ICCSA. Unidades: FM, ICMC
Assuntos: APRENDIZAGEM PROFUNDA, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR IMAGEM, TECNOLOGIAS DA SAÚDE, NEOPLASIAS BUCAIS
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ABNT
SILVA, Arnaldo Vitor Barros da et al. Enhancing explainability in oral cancer detection with Grad-CAM visualizations. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-64605-8_11. Acesso em: 19 nov. 2025. , 2024
APA
Silva, A. V. B. da, Saldivia-Siracusa, C., Souza, E. S. C. de, Araujo, A. L. D., Lopes, M. A., Vargas, P. A., et al. (2024). Enhancing explainability in oral cancer detection with Grad-CAM visualizations. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-031-64605-8_11
NLM
Silva AVB da, Saldivia-Siracusa C, Souza ESC de, Araujo ALD, Lopes MA, Vargas PA, Kowalski LP, Santos-Silva AR dos, Carvalho ACP de LF de, Quiles MG. Enhancing explainability in oral cancer detection with Grad-CAM visualizations [Internet]. Lecture Notes in Computer Science. 2024 ; 14813 151-164.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1007/978-3-031-64605-8_11
Vancouver
Silva AVB da, Saldivia-Siracusa C, Souza ESC de, Araujo ALD, Lopes MA, Vargas PA, Kowalski LP, Santos-Silva AR dos, Carvalho ACP de LF de, Quiles MG. Enhancing explainability in oral cancer detection with Grad-CAM visualizations [Internet]. Lecture Notes in Computer Science. 2024 ; 14813 151-164.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1007/978-3-031-64605-8_11
Trabalho de evento-anais periodico
Applying LSTM recurrent neural networks to predict revenue (2024)
Cardoso, Luis Eduardo Pelin ; Carvalho, Andre Carlos Ponce de Leon Ferreira de ; Quiles, Marcos Gonçalves
Fonte: Lecture Notes in Computer Science. Nome do evento: International Conference on Computational Science and its Applications - ICCSA. Unidade: ICMC
Assuntos: PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), REDES NEURAIS, PREVISÃO DE VENDAS
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ABNT
CARDOSO, Luis Eduardo Pelin e CARVALHO, Andre Carlos Ponce de Leon Ferreira de e QUILES, Marcos Gonçalves. Applying LSTM recurrent neural networks to predict revenue. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-64608-9_13. Acesso em: 19 nov. 2025. , 2024
APA
Cardoso, L. E. P., Carvalho, A. C. P. de L. F. de, & Quiles, M. G. (2024). Applying LSTM recurrent neural networks to predict revenue. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-031-64608-9_13
NLM
Cardoso LEP, Carvalho ACP de LF de, Quiles MG. Applying LSTM recurrent neural networks to predict revenue [Internet]. Lecture Notes in Computer Science. 2024 ; 14814 198-212.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1007/978-3-031-64608-9_13
Vancouver
Cardoso LEP, Carvalho ACP de LF de, Quiles MG. Applying LSTM recurrent neural networks to predict revenue [Internet]. Lecture Notes in Computer Science. 2024 ; 14814 198-212.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1007/978-3-031-64608-9_13
Trabalho de evento-anais periodico
Image segmentation by hierarchical layered oriented image foresting transform subject to closeness constraints (2024)
Santos, Luiz Felipe Dolabela ; Kleine, Felipe Augusto de Souza; Miranda, Paulo André Vechiatto de
Fonte: Lecture Notes in Computer Science. Nome do evento: International Conference on Discrete Geometry and Mathematical Morphology - DGMM. Unidade: IME
Assunto: PROCESSAMENTO DE IMAGENS
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ABNT
SANTOS, Luiz Felipe Dolabela e KLEINE, Felipe Augusto de Souza e MIRANDA, Paulo André Vechiatto de. Image segmentation by hierarchical layered oriented image foresting transform subject to closeness constraints. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-57793-2_26. Acesso em: 19 nov. 2025. , 2024
APA
Santos, L. F. D., Kleine, F. A. de S., & Miranda, P. A. V. de. (2024). Image segmentation by hierarchical layered oriented image foresting transform subject to closeness constraints. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-031-57793-2_26
NLM
Santos LFD, Kleine FA de S, Miranda PAV de. Image segmentation by hierarchical layered oriented image foresting transform subject to closeness constraints [Internet]. Lecture Notes in Computer Science. 2024 ; 14605 338-349.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1007/978-3-031-57793-2_26
Vancouver
Santos LFD, Kleine FA de S, Miranda PAV de. Image segmentation by hierarchical layered oriented image foresting transform subject to closeness constraints [Internet]. Lecture Notes in Computer Science. 2024 ; 14605 338-349.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1007/978-3-031-57793-2_26
Trabalho de evento-anais periodico
Generalizing and unifying gray-box combinatorial optimization operators (2024)
Chicano, Francisco; Whitley, Darrell; Ochoa, Gabriela; Tinós, Renato
Fonte: Lecture Notes in Computer Science. Nome do evento: International Conference on Parallel Problem Solving from Nature (PPSN). Unidade: FFCLRP
Assuntos: MATEMÁTICA, OPERADORES, OTIMIZAÇÃO COMBINATÓRIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CHICANO, Francisco et al. Generalizing and unifying gray-box combinatorial optimization operators. Lecture Notes in Computer Science. Hagenberg: Springer International Publishing. Disponível em: https://doi.org/10.1007/978-3-031-70055-2_4. Acesso em: 19 nov. 2025. , 2024
APA
Chicano, F., Whitley, D., Ochoa, G., & Tinós, R. (2024). Generalizing and unifying gray-box combinatorial optimization operators. Lecture Notes in Computer Science. Hagenberg: Springer International Publishing. doi:10.1007/978-3-031-70055-2_4
NLM
Chicano F, Whitley D, Ochoa G, Tinós R. Generalizing and unifying gray-box combinatorial optimization operators [Internet]. Lecture Notes in Computer Science. 2024 ; 15148 52–67.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1007/978-3-031-70055-2_4
Vancouver
Chicano F, Whitley D, Ochoa G, Tinós R. Generalizing and unifying gray-box combinatorial optimization operators [Internet]. Lecture Notes in Computer Science. 2024 ; 15148 52–67.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1007/978-3-031-70055-2_4

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