16 January 2006 Selecting the kernel type for a web-based adaptive image retrieval systems (AIRS)
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Abstract
The goal of this paper is to investigate the selection of the kernel for a Web-based AIRS. Using the Kernel Perceptron learning method, several kernels having polynomial and Gaussian Radial Basis Function (RBF) like forms (6 polynomials and 6 RBFs) are applied to general images represented by color histograms in RGB and HSV color spaces. Experimental results on these collections show that performance varies significantly between different kernel types and that choosing an appropriate kernel is important.
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Anca Doloc-Mihu, Vijay V. Raghavan, "Selecting the kernel type for a web-based adaptive image retrieval systems (AIRS)", Proc. SPIE 6061, Internet Imaging VII, 60610H (16 January 2006); doi: 10.1117/12.643677; https://doi.org/10.1117/12.643677
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