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Archetypal analysis (AA) proposed by Cutler and Breiman in estimates the principal convex hull of a data set. As such AA favors features that constitute representative 'corners' of the data, i.e. distinct aspects or archetypes. We will show that AA enjoys the interpretability of clustering - without being limited to hard assignment and the uniqueness of SVD - without being limited to orthogonal representations...
This paper puts forward a face recognition model combining global and local features which is adapted to small sorts face recognition in the embedded system. The mainly contribution of this paper is to bring out the thought of doing the identification using double-weight. Firstly, extract the features in the whole face picture and the subfields; then, construct different training set for each feature...
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