Titlebook: Machine Learning and Data Mining in Pattern Recognition; First International Petra Perner,Maria Petrou Conference proceedings 1999 Springe

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Advances in Predictive Data Mining Methodsuss some theoretical developments in PAC learning and statistical learning theory leading to the emergence of support vector machines. We then examine some technical advances made in enhancing the performance of the models both in accuracy (boosting, bagging, stacking) and scalability of modeling through distributed model generation.

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A Dynamics of the Hough Transform and Artificial Neural Networksection by the Hough transform, which achieves grouping of sample points as the permutation of data sequence. The theoretical analysis in this paper verifies the reliability of the Hough- transform based template matching for the detection of shapes from a scene.

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Generalised Fuzzy Aggregation Operatorslues in a range [0,w], with . ≠ 1. Then the need arises for the generalization of the aggregetion operators to cope with such membership functions. In this paper we examine the properties of such generalised operators, that make them appropriate for use in Fuzzy reasoning.

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Multi-valued and Universal Binary Neurons: Learning Algorithms, Application to Image Processing and applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN) for solution of the image processing and image analysis problems. Another effective application of the MVN is their use as the basic neurons in the neural networks oriented to the image recognition.

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Applications of Cellular Neural Networks for Shape from Shading Problem. The focus of this paper is to present one new methodology to solve Shape from Shading problem using CNN. Some practical results are presented and briefly discussed, demonstrating the successful operation of the proposed algorithm.

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