An evaluation of fusion techniques for image retrieval of digital images.
Written in 2006; 1,127 words; 5 sources; MLA; $ 39.95
Paper Summary:
This paper discusses fusion techniques for image retrieval of digital images, in particular the technique using support vector machine (SVM). The paper describes an experiment that was run in order to test the stability of this technique and it details the results that were found.
Table of Contents:
Introduction
Fusion Techniques
SVM
Ensemble
Average and Max
Experiment
Conclusion and Observations
From the Paper:
"Against the backdrop of increased digital images, an accurate image retrieval system is in demand and is supported by a number of methods. Classification is one of the most important parts of image retrieval. Of the several classification techniques, Support Vector Machine (SVM) is the most efficient and the most accurate, especially in cases where the number of samples is small [4]. In addition, to transfer data to higher dimensions, SVM can adapt for non-linear boundary problems [5]."
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