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Artigo de periodico
Evaluating brain group structure methods using hierarchical dynamic models (2024)
Costa, Lilia ; Anacleto, Osvaldo ; Nascimento, Diego Carvalho ; Smith, James Q; Queen, Catriona M; Louzada, Francisco ; Nichols, Thomas
Source: Pattern Recognition. Unidade: ICMC
Subjects: TEORIA DOS GRAFOS, ESTUDO DE CASO, MAPEAMENTO CEREBRAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COSTA, Lilia et al. Evaluating brain group structure methods using hierarchical dynamic models. Pattern Recognition, v. 155, p. 1-13, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.patcog.2024.110687. Acesso em: 11 nov. 2025.
APA
Costa, L., Anacleto, O., Nascimento, D. C., Smith, J. Q., Queen, C. M., Louzada, F., & Nichols, T. (2024). Evaluating brain group structure methods using hierarchical dynamic models. Pattern Recognition, 155, 1-13. doi:10.1016/j.patcog.2024.110687
NLM
Costa L, Anacleto O, Nascimento DC, Smith JQ, Queen CM, Louzada F, Nichols T. Evaluating brain group structure methods using hierarchical dynamic models [Internet]. Pattern Recognition. 2024 ; 155 1-13.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2024.110687
Vancouver
Costa L, Anacleto O, Nascimento DC, Smith JQ, Queen CM, Louzada F, Nichols T. Evaluating brain group structure methods using hierarchical dynamic models [Internet]. Pattern Recognition. 2024 ; 155 1-13.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2024.110687
Artigo de periodico
A network classification method based on density time evolution patterns extracted from network automata (2024)
Zielinski, Kallil Miguel Caparroz; Ribas, Lucas Correia ; Machicao, Jeaneth ; Bruno, Odemir Martinez
Source: Pattern Recognition. Unidades: IFSC, EP
Subjects: REDES COMPLEXAS, REDES NEURAIS, VISÃO COMPUTACIONAL, TEXTURA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ZIELINSKI, Kallil Miguel Caparroz et al. A network classification method based on density time evolution patterns extracted from network automata. Pattern Recognition, v. 146, p. 109802-1-109802-13 + supplementary materials, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.patcog.2023.109946. Acesso em: 11 nov. 2025.
APA
Zielinski, K. M. C., Ribas, L. C., Machicao, J., & Bruno, O. M. (2024). A network classification method based on density time evolution patterns extracted from network automata. Pattern Recognition, 146, 109802-1-109802-13 + supplementary materials. doi:10.1016/j.patcog.2023.109946
NLM
Zielinski KMC, Ribas LC, Machicao J, Bruno OM. A network classification method based on density time evolution patterns extracted from network automata [Internet]. Pattern Recognition. 2024 ; 146 109802-1-109802-13 + supplementary materials.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2023.109946
Vancouver
Zielinski KMC, Ribas LC, Machicao J, Bruno OM. A network classification method based on density time evolution patterns extracted from network automata [Internet]. Pattern Recognition. 2024 ; 146 109802-1-109802-13 + supplementary materials.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2023.109946
Artigo de periodico
Meta-learners for few-shot weakly-supervised medical image segmentation (2024)
Oliveira, Hugo Neves de ; Gama, Pedro Henrique Targino ; Bloch, Isabelle ; César Júnior, Roberto Marcondes
Source: Pattern Recognition. Unidade: IME
Subjects: RECONHECIMENTO DE IMAGEM, PROCESSAMENTO DE IMAGENS, IMAGEM POR RESSONÂNCIA MAGNÉTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Hugo Neves de et al. Meta-learners for few-shot weakly-supervised medical image segmentation. Pattern Recognition, v. 153, n. artigo 110471, p. 1-13, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.patcog.2024.110471. Acesso em: 11 nov. 2025.
APA
Oliveira, H. N. de, Gama, P. H. T., Bloch, I., & César Júnior, R. M. (2024). Meta-learners for few-shot weakly-supervised medical image segmentation. Pattern Recognition, 153( artigo 110471), 1-13. doi:10.1016/j.patcog.2024.110471
NLM
Oliveira HN de, Gama PHT, Bloch I, César Júnior RM. Meta-learners for few-shot weakly-supervised medical image segmentation [Internet]. Pattern Recognition. 2024 ; 153( artigo 110471): 1-13.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2024.110471
Vancouver
Oliveira HN de, Gama PHT, Bloch I, César Júnior RM. Meta-learners for few-shot weakly-supervised medical image segmentation [Internet]. Pattern Recognition. 2024 ; 153( artigo 110471): 1-13.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2024.110471
Artigo de periodico
RADAM: texture recognition through randomized aggregated encoding of deep activation maps (2023)
Scabini, Leonardo Felipe dos Santos ; Zielinski, Kallil Miguel Caparroz; Ribas, Lucas Correia ; Gonçalves, Wesley Nunes ; Baets, Bernard De ; Bruno, Odemir Martinez
Source: Pattern Recognition. Unidade: IFSC
Subjects: REDES COMPLEXAS, REDES NEURAIS, VISÃO COMPUTACIONAL, TEXTURA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SCABINI, Leonardo Felipe dos Santos et al. RADAM: texture recognition through randomized aggregated encoding of deep activation maps. Pattern Recognition, v. No 2023, p. 109802-1-109802-13 + supplementary materials, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.patcog.2023.109802. Acesso em: 11 nov. 2025.
APA
Scabini, L. F. dos S., Zielinski, K. M. C., Ribas, L. C., Gonçalves, W. N., Baets, B. D., & Bruno, O. M. (2023). RADAM: texture recognition through randomized aggregated encoding of deep activation maps. Pattern Recognition, No 2023, 109802-1-109802-13 + supplementary materials. doi:10.1016/j.patcog.2023.109802
NLM
Scabini LF dos S, Zielinski KMC, Ribas LC, Gonçalves WN, Baets BD, Bruno OM. RADAM: texture recognition through randomized aggregated encoding of deep activation maps [Internet]. Pattern Recognition. 2023 ; No 2023 109802-1-109802-13 + supplementary materials.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2023.109802
Vancouver
Scabini LF dos S, Zielinski KMC, Ribas LC, Gonçalves WN, Baets BD, Bruno OM. RADAM: texture recognition through randomized aggregated encoding of deep activation maps [Internet]. Pattern Recognition. 2023 ; No 2023 109802-1-109802-13 + supplementary materials.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.patcog.2023.109802

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