Includes bibliographical references (leaves 123-129) / Support Vector Machines (SVMs) are a new supervised classification technique that has its roots in statistical learning theory. It has gained popularity in fields such as machine vision, artificial intelligence, digital image processing and more recently remote sensing. The three commonly used SVMs include linear, polynomial and radial basis function (i.e. Gaussian) classifiers.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/5599 |
| Date | January 2006 |
| Creators | Gidudu, Anthony |
| Contributors | RĪther, Heinz |
| Publisher | University of Cape Town, Faculty of Engineering and the Built Environment, School of Architecture, Planning and Geomatics |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Doctoral Thesis, Doctoral, PhD |
| Format | application/pdf, application/pdf |
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