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18 September 1998 Discriminative eigen targets for automatic target recognition
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Abstract
Three different linear transformations have been examined for their potential use as feature extractors for an automatic target recognition classifier. These transformations are based on a set of eigen targets, which are obtained through one of the following three methods: principal component analysis, the eigen separation transform, or the Fisher linear discriminant. From the sets of eigen targets obtained through each of the above methods, projection values of an input image are computed and fed to one or more multilayer perceptrons (MLPs) for training and testing purposes. With a fixed-structure MLP, each of the different eigen target sets are examined for their effects on the final recognition performance.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lipchen Alex Chan, Nasser M. Nasrabadi, and Don Torrieri "Discriminative eigen targets for automatic target recognition", Proc. SPIE 3371, Automatic Target Recognition VIII, (18 September 1998); https://doi.org/10.1117/12.323853
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