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Professor GILES FOODY's Outputs (104)

One-class classification for monitoring a specific land cover class: SVDD classification of fenland (2007)
Journal Article
Sanchez-Hernandez, C., Boyd, D. S., & Foody, G. M. (2007). One-class classification for monitoring a specific land cover class: SVDD classification of fenland. IEEE Transactions on Geoscience and Remote Sensing, 45(4), https://doi.org/10.1109/TGRS.2006.890414

Remote sensing is a major source of land cover information. Commonly, interest focuses on a single land cover class. Although a conventional multi-class classifier may be used to provide a map depicting the class of interest the analysis is not focus... Read More about One-class classification for monitoring a specific land cover class: SVDD classification of fenland.

Classification accuracy comparison: hypothesis tests and the use of confidence intervals in evaluations of difference, equivalence and non-inferiority
Journal Article
Foody, G. M. Classification accuracy comparison: hypothesis tests and the use of confidence intervals in evaluations of difference, equivalence and non-inferiority. Remote Sensing of Environment, 113(8), https://doi.org/10.1016/j.rse.2009.03.014

The comparison of classification accuracy statements has generally been based upon tests of difference or inequality when other scenarios and approaches may be more appropriate. Procedures for evaluating two scenarios with interest focused on the sim... Read More about Classification accuracy comparison: hypothesis tests and the use of confidence intervals in evaluations of difference, equivalence and non-inferiority.

A relative evaluation of multi-class image classification by support vector machines
Journal Article
Foody, G. M., & Mathur, A. A relative evaluation of multi-class image classification by support vector machines. IEEE Transactions on Geoscience and Remote Sensing, 42(6), https://doi.org/10.1109/TGRS.2004.827257

Support vector machines (SVM) have considerable potential as classifiers of remotely sensed data. A constraint on their application in remote sensing has been their binary nature, requiring multi-class classifications to be based upon a large number... Read More about A relative evaluation of multi-class image classification by support vector machines.