Source: Lecture Notes in Computer Science. Conference titles: Iberoamerican Congress on Pattern Recognition - CIARP. Unidade: ICMC
Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, INTELIGÊNCIA ARTIFICIAL
ABNT
PONTI, Moacir Antonelli e PAPA, João Paulo e LEVADA, Alexandre L. M. A Markov Random Field model for combining optimum-path forest classifiers using decision graphs and game strategy approach. Lecture Notes in Computer Science. Berlin: Springer-Verlag. Disponível em: https://doi.org/10.1007/978-3-642-25085-9. Acesso em: 13 jul. 2025. , 2011APA
Ponti, M. A., Papa, J. P., & Levada, A. L. M. (2011). A Markov Random Field model for combining optimum-path forest classifiers using decision graphs and game strategy approach. Lecture Notes in Computer Science. Berlin: Springer-Verlag. doi:10.1007/978-3-642-25085-9NLM
Ponti MA, Papa JP, Levada ALM. A Markov Random Field model for combining optimum-path forest classifiers using decision graphs and game strategy approach [Internet]. Lecture Notes in Computer Science. 2011 ; 7042 581-590.[citado 2025 jul. 13 ] Available from: https://doi.org/10.1007/978-3-642-25085-9Vancouver
Ponti MA, Papa JP, Levada ALM. A Markov Random Field model for combining optimum-path forest classifiers using decision graphs and game strategy approach [Internet]. Lecture Notes in Computer Science. 2011 ; 7042 581-590.[citado 2025 jul. 13 ] Available from: https://doi.org/10.1007/978-3-642-25085-9