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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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| Опубликовано в: : | J Am Stat Assoc |
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| Главные авторы: | , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
2015
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| Предметы: | |
| Online-ссылка: | 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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