Kernel principal component analysis and thе construction of non-linear active shape models
The use of Kernel Principal Component Analysis to model data distributions in high-dimensional spaces. Kernel principal component analysis, the KPCA algorithm. The embedded sub-manifold. Constructing non-linear ASMs. Articial statistical shape model.
| Рубрика | Биология и естествознание |
| Предмет | Genetics |
| Вид | статья |
| Язык | английский |
| Прислал(а) | Анна |
| Дата добавления | 08.02.2013 |
| Размер файла | 496,8 K |
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