A new decision fusion technique for image classification

In this study, we introduce a new image classification technique using decision fusion. The proposed technique, called Meta-Fuzzified Yield Value (Meta-FYV), is based on two-layer Stacked Generalization (SG) architecture. At the base-layer, the system, receives a set of feature vectors of various dimensions and dynamical ranges and outputs hypotheses through fuzzy transformations. Then, the hypotheses created by the base layer transformations are concatenated for building a regression equation at meta-layer. Experimental evidence indicates that the Meta-FYV is superior compared to one of the most successful Fuzzy SG methods, introduced by Akbas.