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Öğe Classifiers fusion in recognition of wheat varieties(SPRINGER-VERLAG BERLIN, 2007) Raudys, Sarunas; Baykan, Omer Kaan; Babalik, Ahmet; Denisov, Vitalij; Bielskis, Antanas AndriusFive wheat varieties (Bezostaja Cesit1252, Dagdas, Gerek, Kiziltan traded in Konya Exchange of Commerce, Turkey), characterized by nine geometric and three colour descriptive features have been classified by multiple classier system where pair-wise SLP or SV classifiers served as base experts. In addition to standard voting and Hastie and Tibshirani fusion rules, two new ones were suggested that allowed reducing the generalization error up to 5%. In classifying of kernel lots, we may obtain faultless grain recognition.Öğe Multiclass Mineral Recognition Using Similarity Features and Ensembles of Pair-Wise Classifiers(SPRINGER-VERLAG BERLIN, 2010) Kybartas, Rimantas; Baykan, Nurdan Akhan; Yılmaz, Nihat; Raudys, SarunasMineral determination is a basis of the petrography Automatic mineral classification based on digital image, analysis is getting very popular To improve classification accuracy we consider similarity features. complex one stage classfiers and two-stage classifiers based on simple pair-wise classification algorithms Results show that employment of two-stage classifieis with proper parameters or K class single layer perceptron are good choices for mineral classification Similarity features with properly selected parameters allow obtaining non-lineal decision boundaries and lead to sizeable decrease in classification error rate