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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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Statistical Pattern Recognition

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract;

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Statistical Pattern Recognition

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract;

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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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Pattern Classification

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

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Dissimilarity Representation For Pattern Recognition, The

authors have crafted an essential book for every researcher and systems designer studying or developing pattern recognition systems.;

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Statistical Mechanics & Random Walks

In this book, the authors gather and present topical research in the study of statistical mechanics and random walk principles and;

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Graphs for Pattern Recognition

solutions act as building blocks of geometric decision rules for pattern recognition. Infeasible systems of linear inequalities prove to be a key;

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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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Markov Random Field Modeling in Image Analysis

in computer vision, image processing, statistical pattern recognition and applications of MRFs. It is also suitable as a text for advanced courses;

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Graph Classification And Clustering Based On Vector Space Embedding

in pattern recognition and related areas for a long time.;

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Graph-Based Representations in Pattern Recognition

This book constitutes the refereed proceedings of the 9th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern;

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Correlation Pattern Recognition

Correlation is a robust and general technique for pattern recognition and is used in many applications, such as automatic target;

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Correlation Pattern Recognition

Correlation is a robust and general technique for pattern recognition and is used in many applications, such as automatic target;

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Combining Pattern Classifiers

A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature;

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Graph-Based Representations in Pattern Recognition

recognition, image analysis, graph theory, and also the application of graphs to pattern recognition problems in other fields like computational;

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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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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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Bridging The Gap Between Graph Edit Distance And Kernel Machines

combining the flexibility of edit distance-based graph matching with the power of kernel machines for pattern recognition. The authors introduce a;

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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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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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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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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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Statistical and Machine Learning Approaches for Network Analysis

partition biological networks * An introduction to complex networks measures, statistical properties, and models * Modeling for evolving biological;

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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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