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  • Artigo de periodico

    Laplacian coordinates: theory and methods for seeded image segmentation (2021)

    Casaca, Wallace Correa de Oliveira ; Gois, João Paulo ; Batagelo, Harlen ; Taubin, Gabriel ; Nonato, Luis Gustavo

    Source: IEEE Transactions on Pattern Analysis and Machine Intelligence. Unidade: ICMC

    Subjects: PROCESSAMENTO DE IMAGENS, OPERADORES, BENCHMARKS

    PrivadoAcesso à fonteDOIHow to cite
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    • ABNT

      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: 28 nov. 2025.

    • APA

      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 2025 nov. 28 ] 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 2025 nov. 28 ] Available from: https://doi.org/10.1109/TPAMI.2020.2974475

  • Artigo de periodico

    Semisupervised learning of classifiers: theory, algorithms, and their application to human-computer interaction (2004)

    Cohen, Ira; Cozman, Fabio Gagliardi ; Sebe, Nicu; Cirelo, Marcelo Cesar; Huang, Thomas S.; Fellow

    Source: IEEE Transactions on Pattern Analysis and Machine Intelligence. Unidade: EP

    Subjects: APRENDIZADO COMPUTACIONAL, INTERAÇÃO HOMEM-MÁQUINA, RECONHECIMENTO DE IMAGEM, RECONHECIMENTO DE PADRÕES

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    • ABNT

      COHEN, Ira et al. Semisupervised learning of classifiers: theory, algorithms, and their application to human-computer interaction. IEEE Transactions on Pattern Analysis and Machine Intelligence, v. 26, n. 12, p. 1553-1567, 2004Tradução . . Disponível em: https://doi.org/10.1109/tpami.2004.127. Acesso em: 28 nov. 2025.

    • APA

      Cohen, I., Cozman, F. G., Sebe, N., Cirelo, M. C., Huang, T. S., & Fellow,. (2004). Semisupervised learning of classifiers: theory, algorithms, and their application to human-computer interaction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26( 12), 1553-1567. doi:10.1109/tpami.2004.127

    • NLM

      Cohen I, Cozman FG, Sebe N, Cirelo MC, Huang TS, Fellow. Semisupervised learning of classifiers: theory, algorithms, and their application to human-computer interaction [Internet]. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2004 ; 26( 12): 1553-1567.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1109/tpami.2004.127

    • Vancouver

      Cohen I, Cozman FG, Sebe N, Cirelo MC, Huang TS, Fellow. Semisupervised learning of classifiers: theory, algorithms, and their application to human-computer interaction [Internet]. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2004 ; 26( 12): 1553-1567.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1109/tpami.2004.127
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