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Type-2 Fuzzy Graphical Models for Pattern Recognition / by Jia Zeng, Zhi-Qiang Liu.

By: Zeng, Jia., autor.
Contributor(s): Liu, Zhi-Qiang., autor.
Material type: materialTypeLabelE-bookSeries: (Studies in Computational Intelligence,, 1860-949X ;; 591); (Engineering (Springer-11647)).Publisher: Berlin, Heidelberg : Springer International Publishing, 2015Description: 1 recurso en línea (XIII, 201 páginas 112 ilustraciones).ISBN: 9783662446904.Subject: Reconocimiento de formasOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Introduction -- Probabilistic Graphical Models -- Type-2 Fuzzy Sets for Pattern Recognition -- Type-2 Fuzzy Gaussian Mixture Models -- Type-2 Fuzzy Hidden Moarkov Models -- Type-2 Fuzzy Markov Random Fields -- Type-2 Fuzzy Topic Models -- Conclusions and FutureWork.
Abstract: This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería TK7882 .P3 Z464 2015 EB (Browse shelf(Opens below)) Acceso electrónico eBook.12112433
Total holds: 0

Introduction -- Probabilistic Graphical Models -- Type-2 Fuzzy Sets for Pattern Recognition -- Type-2 Fuzzy Gaussian Mixture Models -- Type-2 Fuzzy Hidden Moarkov Models -- Type-2 Fuzzy Markov Random Fields -- Type-2 Fuzzy Topic Models -- Conclusions and FutureWork.

This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.

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