Kybartas, RimantasBaykan, Nurdan AkhanYılmaz, NihatRaudys, Sarunas2020-03-262020-03-262010Kybartas, R., Baykan, N. A., Yılmaz, N., Raudys, S., (2010). Multiclass Mineral Recognition Using Similarity Features and Ensembles of Pair-Wise Classifiers. Lecture Notes in Artificial Intelligence, 6097, 47-56.978-3-642-13024-30302-9743https://hdl.handle.net/20.500.12395/2508923rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems -- JUN 01-04, 2010 -- Cordoba, SPAINMineral 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 rateeninfo:eu-repo/semantics/openAccessMincial ClassificationSingle Layer PerceptionSupport VectorsTwo Stage ClassifiersSimilarity FeaturesConference Object60974756Q3WOS:000281604400006N/A