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- W2041246122 abstract "This paper introduces the use of relevance vector machines (RVMs) for content-based image classification and compares it with the conventional support vector machine (SVM) approach. Different wavelet kernels are included in the formulation of the RVM. We also propose a new wavelet-based feature extraction method that extracts lesser number of features as compared to other wavelet-based feature extraction methods. Experimental results confirm the superiority of RVM over SVM in terms of the trade-off between slightly reduced accuracy but substantially enhanced sparseness of the solution, and also the ease of free parameters tuning." @default.
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- W2041246122 date "2009-07-21" @default.
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- W2041246122 title "Content-based image classification with wavelet relevance vector machines" @default.
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- W2041246122 doi "https://doi.org/10.1007/s00500-009-0477-2" @default.
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