Filtros : "Indexado no Scopus" "NONATO, LUIS GUSTAVO" Removidos: "Chile" "Universität Würzburg (University of Würzburg)" "Associação Nacional de Criadores e Pesquisadores. Ribeirão Preto, SP" "Reino Unido" "Suiça" "ACVIM Forum" Limpar

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  • Source: IEEE Access. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, REPRESENTAÇÃO

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      ORTIGOSSA, Evandro Scudeleti e GONÇALVES, Thales e NONATO, Luis Gustavo. Explainable artificial intelligence (XAI): from theory to methods and applications. IEEE Access, 2024Tradução . . Disponível em: https://doi.org/10.1109/ACCESS.2023.1120000. Acesso em: 13 jul. 2024.
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      Ortigossa, E. S., Gonçalves, T., & Nonato, L. G. (2024). Explainable artificial intelligence (XAI): from theory to methods and applications. IEEE Access. doi:10.1109/ACCESS.2023.1120000
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      Ortigossa ES, Gonçalves T, Nonato LG. Explainable artificial intelligence (XAI): from theory to methods and applications [Internet]. IEEE Access. 2024 ;[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/ACCESS.2023.1120000
    • Vancouver

      Ortigossa ES, Gonçalves T, Nonato LG. Explainable artificial intelligence (XAI): from theory to methods and applications [Internet]. IEEE Access. 2024 ;[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/ACCESS.2023.1120000
  • Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, VISUALIZAÇÃO, MODELOS PARA PROCESSOS ESTOCÁSTICOS

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      XENOPOULOS, Peter et al. Calibrate: interactive analysis of probabilistic model output. IEEE Transactions on Visualization and Computer Graphics, v. 29, n. Ja 2023, p. 853-863, 2023Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2022.3209489. Acesso em: 13 jul. 2024.
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      Xenopoulos, P., Rulff, J., Nonato, L. G., Barr, B., & Silva, C. (2023). Calibrate: interactive analysis of probabilistic model output. IEEE Transactions on Visualization and Computer Graphics, 29( Ja 2023), 853-863. doi:10.1109/TVCG.2022.3209489
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      Xenopoulos P, Rulff J, Nonato LG, Barr B, Silva C. Calibrate: interactive analysis of probabilistic model output [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2023 ; 29( Ja 2023): 853-863.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/TVCG.2022.3209489
    • Vancouver

      Xenopoulos P, Rulff J, Nonato LG, Barr B, Silva C. Calibrate: interactive analysis of probabilistic model output [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2023 ; 29( Ja 2023): 853-863.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/TVCG.2022.3209489
  • Source: Brazilian Journal of Analytical Chemistry. Unidade: ICMC

    Subjects: BIOCOMBUSTÍVEIS, ALGORITMOS, APRENDIZADO COMPUTACIONAL

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      LUNA, Aderval Severino et al. Employing auto-machine learning algorithms for predicting the cold filter plugging and kinematic viscosity at 40 ºC in biodiesel blends using vibrational spectroscopy data. Brazilian Journal of Analytical Chemistry, v. 10, n. 39, p. 52-69, 2023Tradução . . Disponível em: https://doi.org/10.30744/brjac.2179-3425.AR-30-2022. Acesso em: 13 jul. 2024.
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      Luna, A. S., Torres, A. R., Cunha, C. L., Lima, I. C. A. de, & Nonato, L. G. (2023). Employing auto-machine learning algorithms for predicting the cold filter plugging and kinematic viscosity at 40 ºC in biodiesel blends using vibrational spectroscopy data. Brazilian Journal of Analytical Chemistry, 10( 39), 52-69. doi:10.30744/brjac.2179-3425.AR-30-2022
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      Luna AS, Torres AR, Cunha CL, Lima ICA de, Nonato LG. Employing auto-machine learning algorithms for predicting the cold filter plugging and kinematic viscosity at 40 ºC in biodiesel blends using vibrational spectroscopy data [Internet]. Brazilian Journal of Analytical Chemistry. 2023 ; 10( 39): 52-69.[citado 2024 jul. 13 ] Available from: https://doi.org/10.30744/brjac.2179-3425.AR-30-2022
    • Vancouver

      Luna AS, Torres AR, Cunha CL, Lima ICA de, Nonato LG. Employing auto-machine learning algorithms for predicting the cold filter plugging and kinematic viscosity at 40 ºC in biodiesel blends using vibrational spectroscopy data [Internet]. Brazilian Journal of Analytical Chemistry. 2023 ; 10( 39): 52-69.[citado 2024 jul. 13 ] Available from: https://doi.org/10.30744/brjac.2179-3425.AR-30-2022
  • Source: Data Mining and Knowledge Discovery. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, ALGORITMOS

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      RAIMUNDO, Marcos M e NONATO, Luis Gustavo e POCO, Jorge. Mining Pareto-optimal counterfactual antecedents with a branch-and-boundmodel-agnostic algorithm. Data Mining and Knowledge Discovery, 2022Tradução . . Disponível em: https://doi.org/10.1007/s10618-022-00906-4. Acesso em: 13 jul. 2024.
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      Raimundo, M. M., Nonato, L. G., & Poco, J. (2022). Mining Pareto-optimal counterfactual antecedents with a branch-and-boundmodel-agnostic algorithm. Data Mining and Knowledge Discovery. doi:10.1007/s10618-022-00906-4
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      Raimundo MM, Nonato LG, Poco J. Mining Pareto-optimal counterfactual antecedents with a branch-and-boundmodel-agnostic algorithm [Internet]. Data Mining and Knowledge Discovery. 2022 ;[citado 2024 jul. 13 ] Available from: https://doi.org/10.1007/s10618-022-00906-4
    • Vancouver

      Raimundo MM, Nonato LG, Poco J. Mining Pareto-optimal counterfactual antecedents with a branch-and-boundmodel-agnostic algorithm [Internet]. Data Mining and Knowledge Discovery. 2022 ;[citado 2024 jul. 13 ] Available from: https://doi.org/10.1007/s10618-022-00906-4
  • Source: Multimedia Tools and Applications. Unidade: ICMC

    Subjects: VISÃO COMPUTACIONAL, ENCHENTES URBANAS, SEMÂNTICA

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      FERNANDES JUNIOR, Francisco Erivaldo e NONATO, Luis Gustavo e UEYAMA, Jó. A river flooding detection system based on deep learning and computer vision. Multimedia Tools and Applications, v. 81, p. 40231-40251, 2022Tradução . . Disponível em: https://doi.org/10.1007/s11042-022-12813-3. Acesso em: 13 jul. 2024.
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      Fernandes Junior, F. E., Nonato, L. G., & Ueyama, J. (2022). A river flooding detection system based on deep learning and computer vision. Multimedia Tools and Applications, 81, 40231-40251. doi:10.1007/s11042-022-12813-3
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      Fernandes Junior FE, Nonato LG, Ueyama J. A river flooding detection system based on deep learning and computer vision [Internet]. Multimedia Tools and Applications. 2022 ; 81 40231-40251.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1007/s11042-022-12813-3
    • Vancouver

      Fernandes Junior FE, Nonato LG, Ueyama J. A river flooding detection system based on deep learning and computer vision [Internet]. Multimedia Tools and Applications. 2022 ; 81 40231-40251.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1007/s11042-022-12813-3
  • Source: IEEE Computer Graphics and Applications. Unidade: ICMC

    Subjects: CLUSTERS, VISUALIZAÇÃO, APRENDIZADO COMPUTACIONAL

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      YUAN, Jun et al. SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level. IEEE Computer Graphics and Applications, v. 42, n. 6, p. 24-36, 2022Tradução . . Disponível em: https://doi.org/10.1109/MCG.2022.3199727. Acesso em: 13 jul. 2024.
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      Yuan, J., Chan, G. Y. -Y., Barr, B., Overton, K., Rees, K., Nonato, L. G., et al. (2022). SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level. IEEE Computer Graphics and Applications, 42( 6), 24-36. doi:10.1109/MCG.2022.3199727
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      Yuan J, Chan GY-Y, Barr B, Overton K, Rees K, Nonato LG, Bertini E, Silva CT. SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level [Internet]. IEEE Computer Graphics and Applications. 2022 ; 42( 6): 24-36.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/MCG.2022.3199727
    • Vancouver

      Yuan J, Chan GY-Y, Barr B, Overton K, Rees K, Nonato LG, Bertini E, Silva CT. SUBPLEX: a Visual analytics approach to understand local model explanations at the subpopulation level [Internet]. IEEE Computer Graphics and Applications. 2022 ; 42( 6): 24-36.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/MCG.2022.3199727
  • Source: IEEE Access. Unidade: ICMC

    Subjects: RECONHECIMENTO DE PADRÕES, BENCHMARKING, VISÃO COMPUTACIONAL, FALSIFICAÇÃO

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      CONTRERAS, Rodrigo Colnago et al. A new multi-filter framework for texture image representation improvement using set of pattern descriptors to fingerprint liveness detection. IEEE Access, v. 10, p. 117681-117706, 2022Tradução . . Disponível em: https://doi.org/10.1109/ACCESS.2022.3218335. Acesso em: 13 jul. 2024.
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      Contreras, R. C., Nonato, L. G., Boaventura, M., Boaventura, I. A. G., Santos, F. L. dos, Zanin, R. B., & Viana, M. S. (2022). A new multi-filter framework for texture image representation improvement using set of pattern descriptors to fingerprint liveness detection. IEEE Access, 10, 117681-117706. doi:10.1109/ACCESS.2022.3218335
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      Contreras RC, Nonato LG, Boaventura M, Boaventura IAG, Santos FL dos, Zanin RB, Viana MS. A new multi-filter framework for texture image representation improvement using set of pattern descriptors to fingerprint liveness detection [Internet]. IEEE Access. 2022 ; 10 117681-117706.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/ACCESS.2022.3218335
    • Vancouver

      Contreras RC, Nonato LG, Boaventura M, Boaventura IAG, Santos FL dos, Zanin RB, Viana MS. A new multi-filter framework for texture image representation improvement using set of pattern descriptors to fingerprint liveness detection [Internet]. IEEE Access. 2022 ; 10 117681-117706.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/ACCESS.2022.3218335
  • Source: IEEE Transactions on Visualization and Computer Graphics. Unidades: IEA, FFLCH, ICMC

    Subjects: CRIMINALIDADE, ANÁLISE DE SÉRIES TEMPORAIS, ESPAÇO URBANO

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      GARCIA-ZANABRIA, Germain et al. CriPAV: street-level crime patterns analysis and visualization. IEEE Transactions on Visualization and Computer Graphics, v. 28, n. 12, p. 4000-4015, 2022Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2021.3111146. Acesso em: 13 jul. 2024.
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      Garcia-Zanabria, G., Raimundo, M. M. M., Poco, J., Nery, M. B., Silva, C. T., Adorno, S., & Nonato, L. G. (2022). CriPAV: street-level crime patterns analysis and visualization. IEEE Transactions on Visualization and Computer Graphics, 28( 12), 4000-4015. doi:10.1109/TVCG.2021.3111146
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      Garcia-Zanabria G, Raimundo MMM, Poco J, Nery MB, Silva CT, Adorno S, Nonato LG. CriPAV: street-level crime patterns analysis and visualization [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2022 ; 28( 12): 4000-4015.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/TVCG.2021.3111146
    • Vancouver

      Garcia-Zanabria G, Raimundo MMM, Poco J, Nery MB, Silva CT, Adorno S, Nonato LG. CriPAV: street-level crime patterns analysis and visualization [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2022 ; 28( 12): 4000-4015.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/TVCG.2021.3111146
  • Source: EURO Journal on Computational Optimization. Unidades: ICMC, IME

    Subjects: COVID-19, OTIMIZAÇÃO ESTOCÁSTICA, REDES COMPLEXAS

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      NONATO, Luis Gustavo et al. Robot dance: a mathematical optimization platform for intervention against COVID-19 in a complex network. EURO Journal on Computational Optimization, v. 10, p. 1-13, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.ejco.2022.100025. Acesso em: 13 jul. 2024.
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      Nonato, L. G., Peixoto, P. da S., Pereira, T., Sagastizábal, C., & Silva, P. J. S. (2022). Robot dance: a mathematical optimization platform for intervention against COVID-19 in a complex network. EURO Journal on Computational Optimization, 10, 1-13. doi:10.1016/j.ejco.2022.100025
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      Nonato LG, Peixoto P da S, Pereira T, Sagastizábal C, Silva PJS. Robot dance: a mathematical optimization platform for intervention against COVID-19 in a complex network [Internet]. EURO Journal on Computational Optimization. 2022 ; 10 1-13.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1016/j.ejco.2022.100025
    • Vancouver

      Nonato LG, Peixoto P da S, Pereira T, Sagastizábal C, Silva PJS. Robot dance: a mathematical optimization platform for intervention against COVID-19 in a complex network [Internet]. EURO Journal on Computational Optimization. 2022 ; 10 1-13.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1016/j.ejco.2022.100025
  • Source: Proceedings of the National Academy of Sciences - PNAS. Unidade: ICMC

    Subjects: VACINAS, COVID-19, TOMADA DE DECISÃO, TEMPO DE REAÇÃO

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      SILVA, Paulo J. S. et al. Optimized delay of the second COVID-19 vaccine dose reduces ICU admissions. Proceedings of the National Academy of Sciences - PNAS, v. 118, n. 35, p. 1-6, 2021Tradução . . Disponível em: https://doi.org/10.1073/pnas.2104640118. Acesso em: 13 jul. 2024.
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      Silva, P. J. S., Sagastizábal, C., Nonato, L. G., Struchiner, C. J., & Pereira, T. (2021). Optimized delay of the second COVID-19 vaccine dose reduces ICU admissions. Proceedings of the National Academy of Sciences - PNAS, 118( 35), 1-6. doi:10.1073/pnas.2104640118
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      Silva PJS, Sagastizábal C, Nonato LG, Struchiner CJ, Pereira T. Optimized delay of the second COVID-19 vaccine dose reduces ICU admissions [Internet]. Proceedings of the National Academy of Sciences - PNAS. 2021 ; 118( 35): 1-6.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1073/pnas.2104640118
    • Vancouver

      Silva PJS, Sagastizábal C, Nonato LG, Struchiner CJ, Pereira T. Optimized delay of the second COVID-19 vaccine dose reduces ICU admissions [Internet]. Proceedings of the National Academy of Sciences - PNAS. 2021 ; 118( 35): 1-6.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1073/pnas.2104640118
  • Source: IEEE Transactions on Pattern Analysis and Machine Intelligence. Unidade: ICMC

    Subjects: PROCESSAMENTO DE IMAGENS, OPERADORES, BENCHMARKS

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      CASACA, Wallace Correa de Oliveira et al. Laplacian coordinates: theory and methods for seeded image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, v. 48, n. 8, p. 2665-2681, 2021Tradução . . Disponível em: https://doi.org/10.1109/TPAMI.2020.2974475. Acesso em: 13 jul. 2024.
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      Casaca, W. C. de O., Gois, J. P., Batagelo, H., Taubin, G., & Nonato, L. G. (2021). Laplacian coordinates: theory and methods for seeded image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 48( 8), 2665-2681. doi:10.1109/TPAMI.2020.2974475
    • NLM

      Casaca WC de O, Gois JP, Batagelo H, Taubin G, Nonato LG. Laplacian coordinates: theory and methods for seeded image segmentation [Internet]. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2021 ; 48( 8): 2665-2681.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/TPAMI.2020.2974475
    • Vancouver

      Casaca WC de O, Gois JP, Batagelo H, Taubin G, Nonato LG. Laplacian coordinates: theory and methods for seeded image segmentation [Internet]. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2021 ; 48( 8): 2665-2681.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/TPAMI.2020.2974475
  • Source: Journal of Brachial Plexus and Peripheral Nerve Injury. Unidade: ICMC

    Subjects: PLEXO BRAQUIAL, VISUALIZAÇÃO, ANÁLISE DE DADOS

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      LIN, Jasmine J et al. Motion analytics of trapezius muscle activity in an 18-year-old female with extended upper brachial plexus birth palsy. Journal of Brachial Plexus and Peripheral Nerve Injury, v. 16, n. 1, p. e51-e55, 2021Tradução . . Disponível em: https://doi.org/10.1055/s-0041-1731748. Acesso em: 13 jul. 2024.
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      Lin, J. J., Chan, G. Y. -Y., Silva, C. T., Nonato, L. G., Raghavan, P., McGrath, A., & Chu, A. (2021). Motion analytics of trapezius muscle activity in an 18-year-old female with extended upper brachial plexus birth palsy. Journal of Brachial Plexus and Peripheral Nerve Injury, 16( 1), e51-e55. doi:10.1055/s-0041-1731748
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      Lin JJ, Chan GY-Y, Silva CT, Nonato LG, Raghavan P, McGrath A, Chu A. Motion analytics of trapezius muscle activity in an 18-year-old female with extended upper brachial plexus birth palsy [Internet]. Journal of Brachial Plexus and Peripheral Nerve Injury. 2021 ; 16( 1): e51-e55.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1055/s-0041-1731748
    • Vancouver

      Lin JJ, Chan GY-Y, Silva CT, Nonato LG, Raghavan P, McGrath A, Chu A. Motion analytics of trapezius muscle activity in an 18-year-old female with extended upper brachial plexus birth palsy [Internet]. Journal of Brachial Plexus and Peripheral Nerve Injury. 2021 ; 16( 1): e51-e55.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1055/s-0041-1731748
  • Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC

    Subjects: CRIMINALIDADE, ESPAÇO URBANO, APLICAÇÃO DA LEI

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      ZANABRIA, Germain Garcia et al. CrimAnalyzer: understanding crime patterns in São Paulo. IEEE Transactions on Visualization and Computer Graphics, v. 27, n. 4, p. 2313-2328, 2021Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2019.2947515. Acesso em: 13 jul. 2024.
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      Zanabria, G. G., Silveira, J. A., Poco, J., Paiva, A., Nery, M. B., Silva, C. T., et al. (2021). CrimAnalyzer: understanding crime patterns in São Paulo. IEEE Transactions on Visualization and Computer Graphics, 27( 4), 2313-2328. doi:10.1109/TVCG.2019.2947515
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      Zanabria GG, Silveira JA, Poco J, Paiva A, Nery MB, Silva CT, Adorno S, Nonato LG. CrimAnalyzer: understanding crime patterns in São Paulo [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 4): 2313-2328.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/TVCG.2019.2947515
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      Zanabria GG, Silveira JA, Poco J, Paiva A, Nery MB, Silva CT, Adorno S, Nonato LG. CrimAnalyzer: understanding crime patterns in São Paulo [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 4): 2313-2328.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/TVCG.2019.2947515
  • Source: PLOS ONE. Unidade: ICMC

    Subjects: MODELOS EPIDEMIOLOGICOS, MODELOS MATEMÁTICOS, COVID-19, PANDEMIAS

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      SILVA, Paulo J. S. et al. Smart testing and critical care bed sharing for COVID-19 control. PLOS ONE, v. 16, n. 10, p. 1-17, 2021Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0257235. Acesso em: 13 jul. 2024.
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      Silva, P. J. S., Pereira, T., Sagastizábal, C., Nonato, L. G., Cordova, M. M., & Struchiner, C. J. (2021). Smart testing and critical care bed sharing for COVID-19 control. PLOS ONE, 16( 10), 1-17. doi:10.1371/journal.pone.0257235
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      Silva PJS, Pereira T, Sagastizábal C, Nonato LG, Cordova MM, Struchiner CJ. Smart testing and critical care bed sharing for COVID-19 control [Internet]. PLOS ONE. 2021 ; 16( 10): 1-17.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1371/journal.pone.0257235
    • Vancouver

      Silva PJS, Pereira T, Sagastizábal C, Nonato LG, Cordova MM, Struchiner CJ. Smart testing and critical care bed sharing for COVID-19 control [Internet]. PLOS ONE. 2021 ; 16( 10): 1-17.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1371/journal.pone.0257235
  • Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC

    Subjects: TOPOLOGIA, ANÁLISE DE DADOS, PROJEÇÃO

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      DORAISWAMY, Harish et al. TopoMap: a 0-dimensional homology preserving projection of high-dimensional data. IEEE Transactions on Visualization and Computer Graphics, v. 27, n. 2, p. 561-571, 2021Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2020.3030441. Acesso em: 13 jul. 2024.
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      Doraiswamy, H., Tierny, J., Silva, P. J. S., Nonato, L. G., & Silva, C. (2021). TopoMap: a 0-dimensional homology preserving projection of high-dimensional data. IEEE Transactions on Visualization and Computer Graphics, 27( 2), 561-571. doi:10.1109/TVCG.2020.3030441
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      Doraiswamy H, Tierny J, Silva PJS, Nonato LG, Silva C. TopoMap: a 0-dimensional homology preserving projection of high-dimensional data [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 2): 561-571.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/TVCG.2020.3030441
    • Vancouver

      Doraiswamy H, Tierny J, Silva PJS, Nonato LG, Silva C. TopoMap: a 0-dimensional homology preserving projection of high-dimensional data [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 2): 561-571.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1109/TVCG.2020.3030441
  • Source: Atmospheric Pollution Research. Unidades: ICMC, EESC

    Subjects: POLUIÇÃO ATMOSFÉRICA, ANÁLISE DE SÉRIES TEMPORAIS, RECUPERAÇÃO DA INFORMAÇÃO

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      ALEXANDRINA, Eduardo Carlos et al. Analysis and visualization of multidimensional time series: particulate matter (PM10) from São Carlos-SP (Brazil). Atmospheric Pollution Research, v. 10, n. 4, p. 1299-1311, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.apr.2019.03.001. Acesso em: 13 jul. 2024.
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      Alexandrina, E. C., Ortigossa, E. S., Lui, E. S., Gonçalves, J. A. S., Corrêa, N. A., Nonato, L. G., & Aguiar, M. L. (2019). Analysis and visualization of multidimensional time series: particulate matter (PM10) from São Carlos-SP (Brazil). Atmospheric Pollution Research, 10( 4), 1299-1311. doi:10.1016/j.apr.2019.03.001
    • NLM

      Alexandrina EC, Ortigossa ES, Lui ES, Gonçalves JAS, Corrêa NA, Nonato LG, Aguiar ML. Analysis and visualization of multidimensional time series: particulate matter (PM10) from São Carlos-SP (Brazil) [Internet]. Atmospheric Pollution Research. 2019 ; 10( 4): 1299-1311.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1016/j.apr.2019.03.001
    • Vancouver

      Alexandrina EC, Ortigossa ES, Lui ES, Gonçalves JAS, Corrêa NA, Nonato LG, Aguiar ML. Analysis and visualization of multidimensional time series: particulate matter (PM10) from São Carlos-SP (Brazil) [Internet]. Atmospheric Pollution Research. 2019 ; 10( 4): 1299-1311.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1016/j.apr.2019.03.001
  • Source: Computers and Graphics. Unidade: ICMC

    Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, GEOMETRIA COMPUTACIONAL

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      ZANABRIA, Germain Garcia e GOMEZ-NIETO, Erick e NONATO, Luis Gustavo. iStar (i*): an interactive star coordinates approach for high-dimensional data exploration. Computers and Graphics, v. No 2016, p. 107-118, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.cag.2016.08.007. Acesso em: 13 jul. 2024.
    • APA

      Zanabria, G. G., Gomez-Nieto, E., & Nonato, L. G. (2016). iStar (i*): an interactive star coordinates approach for high-dimensional data exploration. Computers and Graphics, No 2016, 107-118. doi:10.1016/j.cag.2016.08.007
    • NLM

      Zanabria GG, Gomez-Nieto E, Nonato LG. iStar (i*): an interactive star coordinates approach for high-dimensional data exploration [Internet]. Computers and Graphics. 2016 ; No 2016 107-118.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1016/j.cag.2016.08.007
    • Vancouver

      Zanabria GG, Gomez-Nieto E, Nonato LG. iStar (i*): an interactive star coordinates approach for high-dimensional data exploration [Internet]. Computers and Graphics. 2016 ; No 2016 107-118.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1016/j.cag.2016.08.007
  • Source: Computers and Graphics. Unidade: ICMC

    Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, GEOMETRIA COMPUTACIONAL

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      CEDRIM, Douglas et al. Depth functions as a quality measure and for steering multidimensional projections. Computers and Graphics, v. No 2016, p. 93-106, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.cag.2016.08.008. Acesso em: 13 jul. 2024.
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      Cedrim, D., Vad, V., Paiva, A., Gröller, M. E., Nonato, L. G., & Castelo, A. (2016). Depth functions as a quality measure and for steering multidimensional projections. Computers and Graphics, No 2016, 93-106. doi:10.1016/j.cag.2016.08.008
    • NLM

      Cedrim D, Vad V, Paiva A, Gröller ME, Nonato LG, Castelo A. Depth functions as a quality measure and for steering multidimensional projections [Internet]. Computers and Graphics. 2016 ; No 2016 93-106.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1016/j.cag.2016.08.008
    • Vancouver

      Cedrim D, Vad V, Paiva A, Gröller ME, Nonato LG, Castelo A. Depth functions as a quality measure and for steering multidimensional projections [Internet]. Computers and Graphics. 2016 ; No 2016 93-106.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1016/j.cag.2016.08.008
  • Source: Journal of New Music Research. Unidade: ICMC

    Subjects: RECUPERAÇÃO DA INFORMAÇÃO, MÚSICA

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      FERREIRA, Martha Dais et al. On accuracy and time processing evaluation of cover song identification systems. Journal of New Music Research, v. 45, n. 4, p. 333-342, 2016Tradução . . Disponível em: https://doi.org/10.1080/09298215.2016.1249490. Acesso em: 13 jul. 2024.
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      Ferreira, M. D., Corrêa, D. C., Grivet, M. A., Santos, G. T. dos, Mello, R. F. de, & Nonato, L. G. (2016). On accuracy and time processing evaluation of cover song identification systems. Journal of New Music Research, 45( 4), 333-342. doi:10.1080/09298215.2016.1249490
    • NLM

      Ferreira MD, Corrêa DC, Grivet MA, Santos GT dos, Mello RF de, Nonato LG. On accuracy and time processing evaluation of cover song identification systems [Internet]. Journal of New Music Research. 2016 ; 45( 4): 333-342.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1080/09298215.2016.1249490
    • Vancouver

      Ferreira MD, Corrêa DC, Grivet MA, Santos GT dos, Mello RF de, Nonato LG. On accuracy and time processing evaluation of cover song identification systems [Internet]. Journal of New Music Research. 2016 ; 45( 4): 333-342.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1080/09298215.2016.1249490
  • Source: Computers and Graphics. Unidade: ICMC

    Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, GEOMETRIA COMPUTACIONAL

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      AMORIM, Elisa et al. Facing the high-dimensions: inverse projection with radial basis functions. Computers and Graphics, v. 48, p. 35-47, 2015Tradução . . Disponível em: https://doi.org/10.1016/j.cag.2015.02.009. Acesso em: 13 jul. 2024.
    • APA

      Amorim, E., Brazil, E. V., Mena-Chalco, J., Velho, L., Nonato, L. G., Samavati, F., & Sousa, M. C. (2015). Facing the high-dimensions: inverse projection with radial basis functions. Computers and Graphics, 48, 35-47. doi:10.1016/j.cag.2015.02.009
    • NLM

      Amorim E, Brazil EV, Mena-Chalco J, Velho L, Nonato LG, Samavati F, Sousa MC. Facing the high-dimensions: inverse projection with radial basis functions [Internet]. Computers and Graphics. 2015 ; 48 35-47.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1016/j.cag.2015.02.009
    • Vancouver

      Amorim E, Brazil EV, Mena-Chalco J, Velho L, Nonato LG, Samavati F, Sousa MC. Facing the high-dimensions: inverse projection with radial basis functions [Internet]. Computers and Graphics. 2015 ; 48 35-47.[citado 2024 jul. 13 ] Available from: https://doi.org/10.1016/j.cag.2015.02.009

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