Titlebook: Hybrid Information Systems; Ajith Abraham,Mario Köppen Conference proceedings 2002 Springer-Verlag Berlin Heidelberg 2002 algorithms.class

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Use of Multi-category Proximal SVM for Data Set Reductionear MPSVM Formulation in an iterative manner we identify the outliers in the data set and eliminate them. A .-Nearest Neighbor (.-NN) classifier is able to classify points using this reduced data set without significant loss of accuracy. We present experiments on a well known large OCR data set to v

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Neural Techniques in Logo Recognition refers to logos, which are scaled, rotated, and have a brightness or contrast variation from the original logo. The system recognises these logos and makes correct judgements regarding their identity. The success rate for this system is about 75 to 80 percent

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Motion Detection Using Cellular Neural Networks local neighborhood. The function of each processor is dependent on the choice of the control and feedback templates. In this paper a new set of templates is introduced. These templates allow the CNN processor to detect object motion in any direction, as well as estimating the motion distance. Expe

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A Multifaceted Investigation into Speech Readingy machines to improve traditional speech recognition systems. We have been following a line of research that started with a simple audio-visual speech recognition system to what is now a multifaceted investigation into speech reading. This paper overviews our feature extraction technique, red exclus

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Monitoring System Security Using Neural Networks and Support Vector Machinesll increased the risk of information system security. Further, vulnerability assessment indicates that future terrorist attacks may take place in the cyberspace to cause mass disruptions. Developing effective methods for preventing and detecting intrusions and misuses, therefore, will be essential f