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Introduction to Statistical Pattern Recognition

This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a;

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Statistical Pattern Recognition

efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material;

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Statistical Pattern Recognition

efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material;

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Applications of Pattern Recognition

This monograph is intended to cover several major applications of pattern recognition. After a brief introduction to pattern recognition;

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Introduction To Pattern Recognition

This book is an introduction to pattern recognition, meant for undergraduate and graduate students in computer science and related fields;

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An Elementary Introduction to Statistical Learning Theory

endeavor from leading researchers in the fields of philosophy and electrical engineering, An Elementary Introduction to Statistical Learning Theory;

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Structural, Syntactic, and Statistical Pattern Recognition

This book constitutes the proceedings of the Joint IAPR International Workshop on Structural Syntactic, and Statistical Pattern Recognition;

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Pattern Recognition and Neural Networks

Ripley brings together two crucial ideas in pattern recognition: statistical methods and machine learning via neural networks. He brings;

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Handbook Of Pattern Recognition And Computer Vision (3rd Edition)

in the field. On the basic methods in pattern recognition and computer vision, topics range from statistical pattern recognition to array;

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Pattern Recognition

discriminant analysis, feature extraction, error estimation, cluster analysis (together sometimes called statistical pattern recognition), grammatical;

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Structural, Syntactic, and Statistical Pattern Recognition

This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern;

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Pattern Recognition and Artificial Intelligence

of pattern recognition and artificial intelligence, such as statistical, structural and syntactic pattern recognition, machine learning, data mining;

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Pattern Recognition in Biology

Pattern recognition is the research area that studies the operation and design of systems that recognise patterns in data. It encloses;

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Pattern Recognition in Nanoscience, Environmental Engineering & Archeology

(together sometimes called statistical pattern recognition), grammatical inference and parsing (sometimes called syntactical pattern recognition;

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Random Graphs for Statistical Pattern Recognition

resource presents: a detailed look at the application of random graphs to pattern recognition; extensive examples of applications of the graphs;

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Introduction To Pattern Recognition And Machine Learning

This book adopts a detailed and methodological algorithmic approach to explain the concepts of pattern recognition. While the text provides;

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Pattern Recognition and Artificial Intelligence

intelligence, such as statistical, structural and syntactic pattern recognition, machine learning, data mining, neural networks, computer vision;

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Introduction to Pattern Recognition

Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition.

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Pattern Recognition and Neural Networks

This 1996 book is a reliable account of the statistical framework for pattern recognition and machine learning. With unparalleled coverage;

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An Introduction to Pattern Recognition and Machine Learning

mathematical development emphasizing simplicity and intuition. Students beginning to explore pattern recognition do not need a suite of mathematically;

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Pattern Recognition

The heart of pattern recognition concepts, methods and applications are explored in this textbook, using statistical, syntactic and neural;

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Pattern Recognition and Computational Intelligence Techniques Using Matlab

This book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way;

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Pattern Recognition

This book constitutes the refereed proceedings of the 35th German Conference on Pattern Recognition, GCPR 2013, held in Saarbrücken;

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Pattern Recognition

learning and pattern recognition; mathematical foundations, statistical data analysis and models; motion and segmentation; pose, face and gesture;

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Pattern Classification

Classification sheds new light on the relationship between seemingly unrelated approaches to pattern recognition, including statistical methods;

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Deterministic Learning Theory for Identification, Recognition, and Control

recognition and pattern-based control processes. The results are applicable to areas such as detection and isolation of oscillation faults, ECG/EEG;

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Deterministic Learning Theory for Identification, Recognition, and Control

dynamical pattern recognition and pattern-based control processes. The results are applicable to areas such as detection and isolation;

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