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  • Source: Journal of Mathematical Imaging and Vision. Unidade: IME

    Subjects: PROCESSAMENTO DE IMAGENS, VISÃO COMPUTACIONAL

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    • ABNT

      BRAZ, Caio de Moraes et al. Optimum cuts in graphs by general fuzzy connectedness with local band constraints. Journal of Mathematical Imaging and Vision, v. 62, n. 5, p. 659-672, 2020Tradução . . Disponível em: https://doi.org/10.1007/s10851-020-00953-w. Acesso em: 05 jun. 2024.
    • APA

      Braz, C. de M., Miranda, P. A. V. de, Ciesielski, K. C., & Cappabianco, F. A. M. (2020). Optimum cuts in graphs by general fuzzy connectedness with local band constraints. Journal of Mathematical Imaging and Vision, 62( 5), 659-672. doi:10.1007/s10851-020-00953-w
    • NLM

      Braz C de M, Miranda PAV de, Ciesielski KC, Cappabianco FAM. Optimum cuts in graphs by general fuzzy connectedness with local band constraints [Internet]. Journal of Mathematical Imaging and Vision. 2020 ; 62( 5): 659-672.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1007/s10851-020-00953-w
    • Vancouver

      Braz C de M, Miranda PAV de, Ciesielski KC, Cappabianco FAM. Optimum cuts in graphs by general fuzzy connectedness with local band constraints [Internet]. Journal of Mathematical Imaging and Vision. 2020 ; 62( 5): 659-672.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1007/s10851-020-00953-w
  • Unidade: IME

    Assunto: CIÊNCIA DA COMPUTAÇÃO

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    • ABNT

      CASTANEDA LEON, Leissi Margarita. Efficient hierarchical layered graph approach for multi-region segmentation. 2019. Tese (Doutorado) – Universidade de São Paulo, São Paulo, 2019. Disponível em: http://www.teses.usp.br/teses/disponiveis/45/45134/tde-12092019-110342/. Acesso em: 05 jun. 2024.
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      Castaneda Leon, L. M. (2019). Efficient hierarchical layered graph approach for multi-region segmentation (Tese (Doutorado). Universidade de São Paulo, São Paulo. Recuperado de http://www.teses.usp.br/teses/disponiveis/45/45134/tde-12092019-110342/
    • NLM

      Castaneda Leon LM. Efficient hierarchical layered graph approach for multi-region segmentation [Internet]. 2019 ;[citado 2024 jun. 05 ] Available from: http://www.teses.usp.br/teses/disponiveis/45/45134/tde-12092019-110342/
    • Vancouver

      Castaneda Leon LM. Efficient hierarchical layered graph approach for multi-region segmentation [Internet]. 2019 ;[citado 2024 jun. 05 ] Available from: http://www.teses.usp.br/teses/disponiveis/45/45134/tde-12092019-110342/
  • Source: Anais estendidos. Conference titles: Conference on Graphics, Patterns and Images - SIBGRAPI. Unidade: IME

    Assunto: PROCESSAMENTO DE IMAGENS

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      MANSILLA, Lucy Alsina Choque e MIRANDA, Paulo André Vechiatto de. Object segmentation by oriented image foresting transform with connectivity constraints. 2019, Anais.. Porto Alegre: SBC, 2019. Disponível em: https://doi.org/10.5753/sibgrapi.est.2019.8305. Acesso em: 05 jun. 2024.
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      Mansilla, L. A. C., & Miranda, P. A. V. de. (2019). Object segmentation by oriented image foresting transform with connectivity constraints. In Anais estendidos. Porto Alegre: SBC. doi:10.5753/sibgrapi.est.2019.8305
    • NLM

      Mansilla LAC, Miranda PAV de. Object segmentation by oriented image foresting transform with connectivity constraints [Internet]. Anais estendidos. 2019 ;[citado 2024 jun. 05 ] Available from: https://doi.org/10.5753/sibgrapi.est.2019.8305
    • Vancouver

      Mansilla LAC, Miranda PAV de. Object segmentation by oriented image foresting transform with connectivity constraints [Internet]. Anais estendidos. 2019 ;[citado 2024 jun. 05 ] Available from: https://doi.org/10.5753/sibgrapi.est.2019.8305
  • Source: Mathematical Morphology and Its Applications to Signal and Image Processing: Proceedings. Conference titles: International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing -ISMM. Unidade: IME

    Assunto: PROCESSAMENTO DE IMAGENS

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      CONDORI, Marcos A. T e MANSILLA, Lucy Alsina Choque e MIRANDA, Paulo André Vechiatto de. Bandeirantes: a graph-based approach for curve tracing and boundary tracking. 2017, Anais.. Cham: Springer, 2017. Disponível em: https://doi.org/10.1007/978-3-319-57240-6_8. Acesso em: 05 jun. 2024.
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      Condori, M. A. T., Mansilla, L. A. C., & Miranda, P. A. V. de. (2017). Bandeirantes: a graph-based approach for curve tracing and boundary tracking. In Mathematical Morphology and Its Applications to Signal and Image Processing: Proceedings. Cham: Springer. doi:10.1007/978-3-319-57240-6_8
    • NLM

      Condori MAT, Mansilla LAC, Miranda PAV de. Bandeirantes: a graph-based approach for curve tracing and boundary tracking [Internet]. Mathematical Morphology and Its Applications to Signal and Image Processing: Proceedings. 2017 ;[citado 2024 jun. 05 ] Available from: https://doi.org/10.1007/978-3-319-57240-6_8
    • Vancouver

      Condori MAT, Mansilla LAC, Miranda PAV de. Bandeirantes: a graph-based approach for curve tracing and boundary tracking [Internet]. Mathematical Morphology and Its Applications to Signal and Image Processing: Proceedings. 2017 ;[citado 2024 jun. 05 ] Available from: https://doi.org/10.1007/978-3-319-57240-6_8
  • Source: BMC Bioinformatics. Unidades: IME, IQ, BIOINFORMÁTICA

    Subjects: EXPRESSÃO GÊNICA, BIOQUÍMICA

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      FUJITA, André et al. GEDI: a user-friendly toolbox for analysis of large-scale gene expression data. BMC Bioinformatics, v. 8, n. art. 457, p. 1-7, 2007Tradução . . Disponível em: https://doi.org/10.1186/1471-2105-8-457. Acesso em: 05 jun. 2024.
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      Fujita, A., Sato, J. R., Ferreira, C. E., & Sogayar, M. C. (2007). GEDI: a user-friendly toolbox for analysis of large-scale gene expression data. BMC Bioinformatics, 8( art. 457), 1-7. doi:10.1186/1471-2105-8-457
    • NLM

      Fujita A, Sato JR, Ferreira CE, Sogayar MC. GEDI: a user-friendly toolbox for analysis of large-scale gene expression data [Internet]. BMC Bioinformatics. 2007 ; 8( art. 457): 1-7.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1186/1471-2105-8-457
    • Vancouver

      Fujita A, Sato JR, Ferreira CE, Sogayar MC. GEDI: a user-friendly toolbox for analysis of large-scale gene expression data [Internet]. BMC Bioinformatics. 2007 ; 8( art. 457): 1-7.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1186/1471-2105-8-457
  • Source: BMC Systems Biology. Unidades: IQ, IME, BIOINFORMÁTICA

    Subjects: EXPRESSÃO GÊNICA, BIOQUÍMICA

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      FUJITA, André et al. Modeling gene expression regulatory networks with the sparse vector autoregressive model. BMC Systems Biology, v. 1, n. 39, p. 1-11, 2007Tradução . . Disponível em: https://doi.org/10.1186/1752-0509-1-39. Acesso em: 05 jun. 2024.
    • APA

      Fujita, A., Sato, J. R., Garay-Malpartida, H. M., Yamaguchi, R., Miyano, S., Sogayar, M. C., & Ferreira, C. E. (2007). Modeling gene expression regulatory networks with the sparse vector autoregressive model. BMC Systems Biology, 1( 39), 1-11. doi:10.1186/1752-0509-1-39
    • NLM

      Fujita A, Sato JR, Garay-Malpartida HM, Yamaguchi R, Miyano S, Sogayar MC, Ferreira CE. Modeling gene expression regulatory networks with the sparse vector autoregressive model [Internet]. BMC Systems Biology. 2007 ; 1( 39): 1-11.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1186/1752-0509-1-39
    • Vancouver

      Fujita A, Sato JR, Garay-Malpartida HM, Yamaguchi R, Miyano S, Sogayar MC, Ferreira CE. Modeling gene expression regulatory networks with the sparse vector autoregressive model [Internet]. BMC Systems Biology. 2007 ; 1( 39): 1-11.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1186/1752-0509-1-39
  • Source: Bioinformatics. Unidades: IME, IQ, BIOINFORMÁTICA

    Subjects: EXPRESSÃO GÊNICA, BIOQUÍMICA

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    • ABNT

      FUJITA, André et al. Time-varying modeling of gene expression regulatory networks using the wavelet dynamic vector autoregressive method. Bioinformatics, v. 23, n. 13, p. 1623-1630, 2007Tradução . . Disponível em: https://doi.org/10.1093/bioinformatics/btm151. Acesso em: 05 jun. 2024.
    • APA

      Fujita, A., Sato, J. R., Garay-Malpartida, H. M., Morettin, P. A., Sogayar, M. C., & Ferreira, C. E. (2007). Time-varying modeling of gene expression regulatory networks using the wavelet dynamic vector autoregressive method. Bioinformatics, 23( 13), 1623-1630. doi:10.1093/bioinformatics/btm151
    • NLM

      Fujita A, Sato JR, Garay-Malpartida HM, Morettin PA, Sogayar MC, Ferreira CE. Time-varying modeling of gene expression regulatory networks using the wavelet dynamic vector autoregressive method [Internet]. Bioinformatics. 2007 ; 23( 13): 1623-1630.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1093/bioinformatics/btm151
    • Vancouver

      Fujita A, Sato JR, Garay-Malpartida HM, Morettin PA, Sogayar MC, Ferreira CE. Time-varying modeling of gene expression regulatory networks using the wavelet dynamic vector autoregressive method [Internet]. Bioinformatics. 2007 ; 23( 13): 1623-1630.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1093/bioinformatics/btm151
  • Source: Brazilian Journal of Medical and Biological Research. Unidades: IME, IQ, BIOINFORMÁTICA

    Subjects: BIOINFORMÁTICA, BIOQUÍMICA, GENOMAS

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      FUJITA, André et al. The GATO gene annotation tool for research laboratories. Brazilian Journal of Medical and Biological Research, v. 38, n. 11, p. 1571-1574, 2005Tradução . . Disponível em: https://doi.org/10.1590/S0100-879X2005001100002. Acesso em: 05 jun. 2024.
    • APA

      Fujita, A., Massirer, K. B., Durham, A. M., Ferreira, C. E., & Sogayar, M. C. (2005). The GATO gene annotation tool for research laboratories. Brazilian Journal of Medical and Biological Research, 38( 11), 1571-1574. doi:10.1590/S0100-879X2005001100002
    • NLM

      Fujita A, Massirer KB, Durham AM, Ferreira CE, Sogayar MC. The GATO gene annotation tool for research laboratories [Internet]. Brazilian Journal of Medical and Biological Research. 2005 ; 38( 11): 1571-1574.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1590/S0100-879X2005001100002
    • Vancouver

      Fujita A, Massirer KB, Durham AM, Ferreira CE, Sogayar MC. The GATO gene annotation tool for research laboratories [Internet]. Brazilian Journal of Medical and Biological Research. 2005 ; 38( 11): 1571-1574.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1590/S0100-879X2005001100002

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