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Spatially Weighted Principal Component Analysis for Imaging Classification
The aim of this paper is to develop a supervised dimension reduction framework, called Spatially Weighted Principal Component Analysis (SWPCA), for high dimensional imaging classification. Two main challenges in imaging classification are the high dimensionality of the feature space and the complex...
Sparad:
| I publikationen: | J Comput Graph Stat |
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| Huvudupphovsmän: | , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
2014
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4467033/ https://ncbi.nlm.nih.gov/pubmed/26089629 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/10618600.2014.912135 |
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