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In this paper, a classification scheme based on a one-class kernel principle component analysis (KPCA) model ensemble has been proposed for the classification of medical images.
In this paper, a classification scheme based on a one-class KPCA model ensemble has been proposed for the classification of medical images.
Hellings et al. propose a gradient projection-based solution [12], and Guthy et al. propose a user classification scheme based on perturbation analysis [13], in order to handle the rate balancing problem.
It formerly produced the Soviet Library Bibliographical Classification scheme based on a Marxist-Leninist classification of knowledge.
Figure 1 shows the Classification scheme based on the dimensions of FCO research in air transport.
A simple Bayesian classification scheme based on the IA and IF magnitude was demonstrated in [7].
A two stage classification scheme based on similarity measure and an SVM was used.
Open image in new window Fig. 1 Classification scheme based on dimensions of FCO.
A preliminary radiant system classification scheme based on thermal response time is proposed.
A previously described classification scheme based on density, or comonomer content, was the basis for the choice of blend components.
In 2007 an alternative classification scheme based on the RMR, the Hierarchical Rock Mass Rating (HRMR) was presented.
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