Paper
16 January 2006 Selecting the kernel type for a web-based adaptive image retrieval systems (AIRS)
Anca Doloc-Mihu, Vijay V. Raghavan
Author Affiliations +
Proceedings Volume 6061, Internet Imaging VII; 60610H (2006) https://doi.org/10.1117/12.643677
Event: Electronic Imaging 2006, 2006, San Jose, California, United States
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.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Anca Doloc-Mihu and 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); https://doi.org/10.1117/12.643677
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Cited by 3 scholarly publications.
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KEYWORDS
RGB color model

Image retrieval

Feature extraction

Data processing

Vector spaces

Associative arrays

Computing systems

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