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Is there a preferred classifier for operational thematic mapping?

Richards, John; Kingsbury, Nick G.


The importance of properly exploiting a classifier's inherent geometric characteristics when developing a classification methodology is emphasized as a prerequisite to achieving near optimal performance when carrying out thematic mapping. When used properly, it is argued that the long-standing maximum likelihood approach and the more recent support vector machine can perform comparably. Both contain the flexibility to segment the spectral domain in such a manner as to match inherent class...[Show more]

CollectionsANU Research Publications
Date published: 2014
Type: Journal article
Source: IEEE Transactions on Geoscience and Remote Sensing
DOI: 10.1109/TGRS.2013.2264831


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