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Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVII
The Multi-class Convex-FUMI (Multi-class C-FUMI) method is developed and described. The method is capable of learning prototypes for multiple target classes from hyperspectral imagery. Multi-class C-FUMI is a non-traditional supervised learning method based on the Functions of Multiple Instances (FUMI) concept. The FUMI concept differs significantly from traditional supervised by the assumption that only functions of target patterns are available. Moreover, these functions are likely to involvedoi:10.1117/12.884230 fatcat:vnjy743cuveendu5ixvpguu2wu