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Titlebook: Engineering Applications of Neural Networks; 11th International C Dominic Palmer-Brown,Chrisina Draganova,Haris Mour Conference proceedings

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Municipal Creditworthiness Modelling by Kernel-Based Approaches with Supervised and Semi-supervisedion. A model design includes data pre-processing, labelling of individual parameters’ vectors using expert knowledge, and the design of various support vector machines with supervised learning and kernel-based approaches with semi-supervised learning.
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An Improved Algorithm for SVMs Classification of Imbalanced Data Sets,thetic examples of the minority class. In our experiments, we compared BED with original SVM and Synthetic Minority Oversampling Technique (SMOTE), a popular resampling strategy in the literature. Our results demonstrate that this new approach improves SVM classifier performance on several real worl
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Visualization of MIMO Process Dynamics Using Local Dynamic Modelling with Self Organizing Maps,tanding and for control system design. The proposed approach is applied to an industrial-scale version of the well known 4-tank plant, showing a comparison in terms of estimation accuracy with a global linear estimator and with a NARX (Nonlinear Auto-Regressive with eXogenous input) estimator based
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Relating Halftone Dot Quality to Paper Surface Topography,are divided into high and low print quality. Features from the unprinted paper surface topography are then used to classify the corresponding paper areas using Support Vector Machine classification. The results show that the topography of the paper can explain some of the print defects. However, the
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Discriminating Angry, Happy and Neutral Facial Expression: A Comparison of Computational Models,ith better accuracy.  Moreover we can achieve this with data that has been massively reduced in size: in the best case the original images are reduced to just 5 components with happy faces and 5 components with angry faces.
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1865-0929 40% of submitted papers for fu- length presentation at the conference. All members of the Program Committee were asked to participate in the reviewing process.978-3-642-03968-3978-3-642-03969-0Series ISSN 1865-0929 Series E-ISSN 1865-0937
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