Introduction To Pattern Recognition

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Pattern Recognition And Classification

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Author : Geoff Dougherty
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-10-28

Pattern Recognition And Classification written by Geoff Dougherty and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-28 with Computers categories.

The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer vision. Fundamental concepts of supervised and unsupervised classification are presented in an informal, rather than axiomatic, treatment so that the reader can quickly acquire the necessary background for applying the concepts to real problems. More advanced topics, such as semi-supervised classification, combining clustering algorithms and relevance feedback are addressed in the later chapters. This book is suitable for undergraduates and graduates studying pattern recognition and machine learning.

Introduction To Pattern Recognition

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Author : Sergios Theodoridis
language : en
Publisher: Academic Press
Release Date : 2010-03-03

Introduction To Pattern Recognition written by Sergios Theodoridis and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-03 with Computers categories.

Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition. It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision. - Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition, Fourth Edition - Solved examples in Matlab, including real-life data sets in imaging and audio recognition - Available separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3)

Introduction To Pattern Recognition

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Author : Menahem Friedman
language : en
Publisher: World Scientific
Release Date : 1999

Introduction To Pattern Recognition written by Menahem Friedman and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.

This book is an introduction to pattern recognition, meant for undergraduate and graduate students in computer science and related fields in science and technology. Most of the topics are accompanied by detailed algorithms and real world applications. In addition to statistical and structural approaches, novel topics such as fuzzy pattern recognition and pattern recognition via neural networks are also reviewed. Each topic is followed by several examples solved in detail. The only prerequisites for using this book are a one-semester course in discrete mathematics and a knowledge of the basic preliminaries of calculus, linear algebra and probability theory.

Introduction To Pattern Recognition And Machine Learning

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Author : M Narasimha Murty
language : en
Publisher: World Scientific
Release Date : 2015-04-22

Introduction To Pattern Recognition And Machine Learning written by M Narasimha Murty and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-22 with Computers categories.

This book adopts a detailed and methodological algorithmic approach to explain the concepts of pattern recognition. While the text provides a systematic account of its major topics such as pattern representation and nearest neighbour based classifiers, current topics — neural networks, support vector machines and decision trees — attributed to the recent vast progress in this field are also dealt with. Introduction to Pattern Recognition and Machine Learning will equip readers, especially senior computer science undergraduates, with a deeper understanding of the subject matter.

Pattern Recognition And Machine Learning

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Author : Y. Anzai
language : en
Publisher: Elsevier
Release Date : 2012-12-02

Pattern Recognition And Machine Learning written by Y. Anzai and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-02 with Computers categories.

This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

Pattern Recognition

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Author : J.P. Marques de Sá
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Pattern Recognition written by J.P. Marques de Sá and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

Pattern recognition currently comprises a vast body of methods supporting the development of numerous applications in many different areas of activity. The generally recognized relevance of pattern recognition methods and techniques lies, for the most part, in the general trend of "intelligent" task emulation, which has definitely pervaded our daily life. Robot assisted manufacture, medical diagnostic systems, forecast of economic variables, exploration of Earth's resources, and analysis of satellite data are just a few examples of activity fields where this trend applies. The pervasiveness of pattern recognition has boosted the number of task specific methodologies and enriched the number of links with other disciplines. As counterbalance to this dispersive tendency there have been, more recently, new theoretical developments that are bridging together many of the classical pattern recognition methods and presenting a new perspective of their links and inner workings. This book has its origin in an introductory course on pattern recognition taught at the Electrical and Computer Engineering Department, Oporto University. From the initial core of this course, the book grew with the intent of presenting a comprehensive and articulated view of pattern recognition methods combined with the intent of clarifying practical issues with the aid of examples and applications to real-life data. The book is primarily addressed to undergraduate and graduate students attending pattern recognition courses of engineering and computer science curricula.

Statistical Pattern Recognition

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Author : Andrew R. Webb
language : en
Publisher: John Wiley & Sons
Release Date : 2003-07-25

Statistical Pattern Recognition written by Andrew R. Webb and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-07-25 with Mathematics categories.

Statistical pattern recognition is a very active area of study andresearch, which has seen many advances in recent years. New andemerging applications - such as data mining, web searching,multimedia data retrieval, face recognition, and cursivehandwriting recognition - require robust and efficient patternrecognition techniques. Statistical decision making and estimationare regarded as fundamental to the study of pattern recognition. Statistical Pattern Recognition, Second Edition has been fullyupdated with new methods, applications and references. It providesa comprehensive introduction to this vibrant area - with materialdrawn from engineering, statistics, computer science and the socialsciences - and covers many application areas, such as databasedesign, artificial neural networks, and decision supportsystems. * Provides a self-contained introduction to statistical patternrecognition. * Each technique described is illustrated by real examples. * Covers Bayesian methods, neural networks, support vectormachines, and unsupervised classification. * Each section concludes with a description of the applicationsthat have been addressed and with further developments of thetheory. * Includes background material on dissimilarity, parameterestimation, data, linear algebra and probability. * Features a variety of exercises, from 'open-book' questions tomore lengthy projects. The book is aimed primarily at senior undergraduate and graduatestudents studying statistical pattern recognition, patternprocessing, neural networks, and data mining, in both statisticsand engineering departments. It is also an excellent source ofreference for technical professionals working in advancedinformation development environments. For further information on the techniques and applicationsdiscussed in this book please visit ahref="http://www.statistical-pattern-recognition.net/"www.statistical-pattern-recognition.net/a

Syntactic And Structural Pattern Recognition

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Author : Horst Bunke
language : en
Publisher: World Scientific
Release Date : 1990

Syntactic And Structural Pattern Recognition written by Horst Bunke and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Computers categories.

This book is currently the only one on this subject containing both introductory material and advanced recent research results. It presents, at one end, fundamental concepts and notations developed in syntactic and structural pattern recognition and at the other, reports on the current state of the art with respect to both methodology and applications. In particular, it includes artificial intelligence related techniques, which are likely to become very important in future pattern recognition.The book consists of individual chapters written by different authors. The chapters are grouped into broader subject areas like “Syntactic Representation and Parsing”, “Structural Representation and Matching”, “Learning”, etc. Each chapter is a self-contained presentation of one particular topic. In order to keep the original flavor of each contribution, no efforts were undertaken to unify the different chapters with respect to notation. Naturally, the self-containedness of the individual chapters results in some redundancy. However, we believe that this handicap is compensated by the fact that each contribution can be read individually without prior study of the preceding chapters. A unification of the spectrum of material covered by the individual chapters is provided by the subject and author index included at the end of the book.

Decision Estimation And Classification

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Author : Charles W. Therrien
language : en
Publisher:
Release Date : 1989-01-17

Decision Estimation And Classification written by Charles W. Therrien and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989-01-17 with Computers categories.

Very Good,No Highlights or Markup,all pages are intact.