2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)
DOI: 10.1109/icassp.2000.859305
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Adaptive local feature based classification for multispectral data

Abstract: In this paper, a new adaptive feature selection based supervised classification technique in which features are selected locally rather than globally as in Principal Component Analysis (PCA) and Minimum Component Analysis (MCA) is presented. Classification techniques based on such global parameters tends to degrade because all classes are projected along the principal component direction for PCA and minimum component direction for MCA. All the classes are projected along these directions under the assumption t… Show more

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