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Semi-supervised Cluster Analysis of Imaging Data
In this paper, we present a semi-supervised clustering-based framework for discovering coherent subpopulations in heterogeneous image sets. Our approach involves limited supervision in the form of labeled instances from two distributions that reflect a rough guess about subspace of features that are...
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| Hlavní autoři: | , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2010
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3008313/ https://ncbi.nlm.nih.gov/pubmed/20933091 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2010.09.074 |
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