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Filtros : "ALGORITMOS" "FO-ODE" Limpar

Filtros

Artigo de periodico
Root Coverage for Single Deep Gingival Recessions: outcomes Based on a Decision-Making Algorithm (2019)
César Neto, João Batista; Cavalcanti, Marília Cabral; Sekiguchi, Ricardo Takiy; Pannuti, Cláudio Mendes; Romito, Giuseppe Alexandre; Tatakis, Dimitris N
Source: International Journal of Dentistry. Unidade: FO
Subjects: RETRAÇÃO GENGIVAL, ALGORITMOS, TOMADA DE DECISÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CÉSAR NETO, João Batista et al. Root Coverage for Single Deep Gingival Recessions: outcomes Based on a Decision-Making Algorithm. International Journal of Dentistry, n. Ja 2019, 2019Tradução . . Disponível em: https://doi.org/10.1155/2019/1830765. Acesso em: 13 nov. 2024.
APA
César Neto, J. B., Cavalcanti, M. C., Sekiguchi, R. T., Pannuti, C. M., Romito, G. A., & Tatakis, D. N. (2019). Root Coverage for Single Deep Gingival Recessions: outcomes Based on a Decision-Making Algorithm. International Journal of Dentistry, ( Ja 2019). doi:10.1155/2019/1830765
NLM
César Neto JB, Cavalcanti MC, Sekiguchi RT, Pannuti CM, Romito GA, Tatakis DN. Root Coverage for Single Deep Gingival Recessions: outcomes Based on a Decision-Making Algorithm [Internet]. International Journal of Dentistry. 2019 ;( Ja 2019):[citado 2024 nov. 13 ] Available from: https://doi.org/10.1155/2019/1830765
Vancouver
César Neto JB, Cavalcanti MC, Sekiguchi RT, Pannuti CM, Romito GA, Tatakis DN. Root Coverage for Single Deep Gingival Recessions: outcomes Based on a Decision-Making Algorithm [Internet]. International Journal of Dentistry. 2019 ;( Ja 2019):[citado 2024 nov. 13 ] Available from: https://doi.org/10.1155/2019/1830765
Artigo de periodico
K-means and Hierarchical Cluster Analysis as segmentation algorithms of FTIR hyperspectral images collected from cutaneous tissue (2018)
Lima, Cassio; Corrêa, Luciana; Byrne, Hugh; Zezzel, Denise
Source: IEEE Proceedings. Unidade: FO
Subjects: ESPECTROSCOPIA, ALGORITMOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LIMA, Cassio et al. K-means and Hierarchical Cluster Analysis as segmentation algorithms of FTIR hyperspectral images collected from cutaneous tissue. IEEE Proceedings, 2018Tradução . . Disponível em: https://doi.org/10.1109/SBFoton-IOPC.2018.8610920. Acesso em: 13 nov. 2024.
APA
Lima, C., Corrêa, L., Byrne, H., & Zezzel, D. (2018). K-means and Hierarchical Cluster Analysis as segmentation algorithms of FTIR hyperspectral images collected from cutaneous tissue. IEEE Proceedings. doi:10.1109/SBFoton-IOPC.2018.8610920
NLM
Lima C, Corrêa L, Byrne H, Zezzel D. K-means and Hierarchical Cluster Analysis as segmentation algorithms of FTIR hyperspectral images collected from cutaneous tissue [Internet]. IEEE Proceedings. 2018 ;[citado 2024 nov. 13 ] Available from: https://doi.org/10.1109/SBFoton-IOPC.2018.8610920
Vancouver
Lima C, Corrêa L, Byrne H, Zezzel D. K-means and Hierarchical Cluster Analysis as segmentation algorithms of FTIR hyperspectral images collected from cutaneous tissue [Internet]. IEEE Proceedings. 2018 ;[citado 2024 nov. 13 ] Available from: https://doi.org/10.1109/SBFoton-IOPC.2018.8610920

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