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The research presented in this paper refers to classification of geometric shapes (cubes, pyramids and cylinders) using multilayer neural network. The input data of the algorithm are the images of shapes placed in different positions and distances from the camera. The classification is based on feature vectors that are obtained using methods of digital image processing. Feature vectors are inputs...
Modern studies of a cultural heritage objects are increasingly multidisciplinary. A variety of analytical techniques supported by pattern recognition methods can help in answering about the origin, dating or authenticity. Results of sourcing ceramics from three Neolithic sites in Serbia are shown in this paper. The procedure based on radial basic function networks (RBFN) was employed in ceramic characterization...
Many decision making problems can be formulated as pattern classification problems. Therefore, high performing classification algorithms are highly sought after. Rule based pattern classification algorithms have an advantage that they do not appear to the user just as a “black box” but may provide additional insight based on the generated rules. In this paper, we focus on fuzzy rule based approaches...
Medical data classification is acknowledged as an area of increasing importance, yet also poses many difficulties. One of these is that medical datasets are often imbalanced; that is that there are (potentially many) more samples of some classes compared to others. In this paper, a dedicated algorithm - Undersampling Balanced Ensemble (USBE) - is used to deal with this problem. We then conduct an...
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