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Titlebook: Advanced Machine Learning Technologies and Applications; Second International Aboul Ella Hassanien,Mohamed F. Tolba,Ahmad Taher Conference

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Arabic Text Recognition Based on Neuro-Genetic Feature Selection Approach Hauptdimensionen der Produktivitätsbetrachtung dieser Arbeit und werden schließlich in einem Effizienz-Ressourcen-Portfolio zusammengeführt, das die Positionierung der Anlagensysteme entsprechend der jeweiligen Ausprägung ermöglicht (Kap. 3.3.).
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https://doi.org/10.1007/978-3-319-13461-1Arabic character recognition; CBR; artificial intelligence; cloud computing; computational intelligence;
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978-3-319-13460-4Springer International Publishing Switzerland 2014
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https://doi.org/10.1007/978-3-319-53300-1n be described as a tool to distinguish an object of one class from another object of another class. It is necessary to define the significant primitives. The size of vector primitives can be large if a large number of primitives are extracted including redundant and irrelevant features. As a result
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State of the Science in Big Data Analyticscted features, which in turn determines the efficient and appropriate classifier for each system. This study is an investigation of using both K- Nearest Neighbor (KNN) and Random Forest Tree (RFT) classifiers with previously tested statistical features. These features are independent of the fonts a
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https://doi.org/10.1007/978-3-319-53300-1ortant step in an OCR system. Support Vectors Machines (SVM) is among the tool of classification that appears these days. This tool proves its ability to discriminate between the forms and gives encouraging result. In this paper, we present an overview of the Arabic optical character recognition (AO
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State of the Science in Big Data Analyticsl media and photography. While some camera-based approaches provided partial solutions for the visually impaired, they still constitute a cumbersome process for the user. iSee is an Android based application that benefits from the commercially available technology to help the visually impaired peopl
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