K-means and Hierarchical Cluster Analysis as segmentation algorithms of FTIR hyperspectral images collected from cutaneous tissue (2018)
- Authors:
- Autor USP: CORRÊA, LUCIANA - FO
- Unidade: FO
- DOI: 10.1109/SBFoton-IOPC.2018.8610920
- Subjects: ESPECTROSCOPIA; ALGORITMOS
- Language: Inglês
- Imprenta:
- Source:
- Título: IEEE Proceedings
- Volume/Número/Paginação/Ano: Online, 2018
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
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: 25 jan. 2026. -
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 2026 jan. 25 ] 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 2026 jan. 25 ] Available from: https://doi.org/10.1109/SBFoton-IOPC.2018.8610920 - Severe oral infection caused by Pseudomonas aeruginosa effectively treated with methylene blue-mediated photodynamic inactivation
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Informações sobre o DOI: 10.1109/SBFoton-IOPC.2018.8610920 (Fonte: oaDOI API)
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