ISBN: 9783319305134 - search techniques in intelligent classification systems (springerbriefs in optimization) (15 resultados)

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Condición: New. pp. 96 1st ed. 2016 edition NO-PA16APR2015-KAP.

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - A unified methodology for categorizing various complexobjects is presented in this book. Through probability theory, novelasymptotically minimax criteria suitable for practical applications in imagingand data analysis are examined including the special cases such as theJensen-Shannon divergence and the probabilistic neural network. An optimalapproximate nearest neighbor search algorithm, which allows fasterclassification of databases is featured. Rough set theory, sequential analysisand granular computing are used to improve performance of the hierarchicalclassifiers. Practical examples in face identification (including deep neuralnetworks), isolated commands recognition in voice control system andclassification of visemes captured by the Kinect depth camera are included.This approach creates fast and accurate search procedures by using exactprobability densities of applied dissimilarity measures.Thisbook can be used as a guide for independent study and as supplementary materialfor a technically oriented graduate course in intelligent systems and datamining. Students and researchers interested in the theoretical and practicalaspects of intelligent classification systems will find answers to:- Why conventional implementation of the naive Bayesianapproach does not work well in image classification - How to deal with insufficient performance of hierarchicalclassification systems - Is it possible to prevent an exhaustive search of thenearest neighbor in a database.…

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A unified methodology for categorizing various complexobjects is presented in this book. Through probability theory, novelasymptotically minimax criteria suitable for practical applications in imagingand data analysis are examined including the special cases such as theJensen-Shannon divergence and the probabilistic neural network. An optimalapproximate nearest neighbor search algorithm, which allows fasterclassification of databases is featured. Rough set theory, sequential analysisand granular computing are used to improve performance of the hierarchicalclassifiers. Practical examples in face identification (including deep neuralnetworks), isolated commands recognition in voice control system andclassification of visemes captured by the Kinect depth camera are included.This approach creates fast and accurate search procedures by using exactprobability densities of applied dissimilarity measures.Thisbook can be used as a guide for independent study and as supplementary materialfor a technically oriented graduate course in intelligent systems and datamining. Students and researchers interested in the theoretical and practicalaspects of intelligent classification systems will find answers to:- Why conventional implementation of the naive Bayesianapproach does not work well in image classification - How to deal with insufficient performance of hierarchicalclassification systems - Is it possible to prevent an exhaustive search of thenearest neighbor in a database 96 pp. Englisch.…

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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Unifies theory and practice: from statistically optimal criteria to applications in image and speech recognitionDescribes methodology of segment homogeneity testing to uniformly solve classification problemsContains practical aspects of mod.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -A unified methodology for categorizing various complexobjects is presented in this book. Through probability theory, novelasymptotically minimax criteria suitable for practical applications in imagingand data analysis are examined including the special cases such as theJensen-Shannon divergence and the probabilistic neural network. An optimalapproximate nearest neighbor search algorithm, which allows fasterclassification of databases is featured. Rough set theory, sequential analysisand granular computing are used to improve performance of the hierarchicalclassifiers. Practical examples in face identification (including deep neuralnetworks), isolated commands recognition in voice control system andclassification of visemes captured by the Kinect depth camera are included.This approach creates fast and accurate search procedures by using exactprobability densities of applied dissimilarity measures.Thisbook can be used as a guide for independent study and as supplementary materialfor a technically oriented graduate course in intelligent systems and datamining. Students and researchers interested in the theoretical and practicalaspects of intelligent classification systems will find answers to: Why conventional implementation of the naive Bayesianapproach does not work well in image classification How to deal with insufficient performance of hierarchicalclassification systems Is it possible to prevent an exhaustive search of thenearest neighbor in a database Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 96 pp. Englisch.…