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Clustering High-Dimensional Landmark-based Two-dimensional Shape Data(‡)
An important goal in image analysis is to cluster and recognize objects of interest according to the shapes of their boundaries. Clustering such objects faces at least four major challenges including a curved shape space, a high-dimensional feature space, a complex spatial correlation structure, and...
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| Publicado no: | J Am Stat Assoc |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2015
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4654964/ https://ncbi.nlm.nih.gov/pubmed/26604425 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2015.1034802 |
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