Pattern Classification

Pattern Classification PDF Author: Richard O. Duda
Publisher: John Wiley & Sons
ISBN: 111858600X
Category : Technology & Engineering
Languages : en
Pages : 680

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Book Description
The first edition, published in 1973, has become a classicreference in the field. Now with the second edition, readers willfind information on key new topics such as neural networks andstatistical pattern recognition, the theory of machine learning,and the theory of invariances. Also included are worked examples,comparisons between different methods, extensive graphics, expandedexercises and computer project topics. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.

Pattern Classification

Pattern Classification PDF Author: Richard O. Duda
Publisher: John Wiley & Sons
ISBN: 111858600X
Category : Technology & Engineering
Languages : en
Pages : 680

Get Book Here

Book Description
The first edition, published in 1973, has become a classicreference in the field. Now with the second edition, readers willfind information on key new topics such as neural networks andstatistical pattern recognition, the theory of machine learning,and the theory of invariances. Also included are worked examples,comparisons between different methods, extensive graphics, expandedexercises and computer project topics. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.

Classification, 2nd Edition

Classification, 2nd Edition PDF Author: A.D. Gordon
Publisher: CRC Press
ISBN: 9781584888536
Category : Mathematics
Languages : en
Pages : 274

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Book Description
As the amount of information recorded and stored electronically grows ever larger, it becomes increasingly useful, if not essential, to develop better and more efficient ways to summarize and extract information from these large, multivariate data sets. The field of classification does just that-investigates sets of "objects" to see if they can be summarized into a small number of classes comprising similar objects. Researchers have made great strides in the field over the last twenty years, and classification is no longer perceived as being concerned solely with exploratory analyses. The second edition of Classification incorporates many of the new and powerful methodologies developed since its first edition. Like its predecessor, this edition describes both clustering and graphical methods of representing data, and offers advice on how to decide which methods of analysis best apply to a particular data set. It goes even further, however, by providing critical overviews of recent developments not widely known, including efficient clustering algorithms, cluster validation, consensus classifications, and the classification of symbolic data. The author has taken an approach accessible to researchers in the wide variety of disciplines that can benefit from classification analysis and methods. He illustrates the methodologies by applying them to data sets-smaller sets given in the text, larger ones available through a Web site. Large multivariate data sets can be difficult to comprehend-the sheer volume and complexity can prove overwhelming. Classification methods provide efficient, accurate ways to make them less unwieldy and extract more information. Classification, Second Edition offers the ideal vehicle for gaining the background and learning the methodologies-and begin putting these techniques to use.

Classification of Life

Classification of Life PDF Author: Melissa Stewart
Publisher: Twenty-First Century Books
ISBN: 0822566044
Category : Juvenile Nonfiction
Languages : en
Pages : 84

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Book Description
Tells the story of how the science of classification has revolutionized the way we look at life on our planet.

Essential Classification

Essential Classification PDF Author: Vanda Broughton
Publisher: Facet Publishing
ISBN: 1783300310
Category : Language Arts & Disciplines
Languages : en
Pages : 433

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Book Description
Classification is a crucial skill for all information workers involved in organizing collections. This new edition offers fully revised and updated guidance on how to go about classifying a document from scratch. Essential Classification leads the novice classifier step by step through the basics of subject cataloguing, with an emphasis on practical document analysis and classification. It deals with fundamental questions of the purpose of classification in different situations, and the needs and expectations of end users. The reader is introduced to the ways in which document content can be assessed, and how this can best be expressed for translation into the language of specific indexing and classification systems. Fully updated to reflect changes to the major general schemes (Library of Congress, LCSH, Dewey and UDC) since the first edition, and with new chapters on working with informal classification, from folksonomies to tagging and social media, this new edition will set cataloguers on the right path. Key areas covered are: - The need for classification - The variety of classification - The structure of classification - Working with informal classification - Management aspects of classification - Classification in digital space. This guide is essential reading for library school students, novice cataloguers and all information workers who need to classify but have not formally been taught how. It also offers practical guidance to computer scientists, internet and intranet managers, and all others concerned with the design and maintenance of subject tools.

Shape Classification and Analysis

Shape Classification and Analysis PDF Author: Luciano da Fona Costa
Publisher: CRC Press
ISBN: 0849379407
Category : Technology & Engineering
Languages : en
Pages : 693

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Book Description
Because the properties of objects are largely determined by their geometric features, shape analysis and classification are essential to almost every applied scientific and technological area. A detailed understanding of the geometrical features of real-world entities (e.g., molecules, organs, materials and components) can provide important clues about their origin and function. When properly and carefully applied, shape analysis offers an exceedingly rich potential to yield useful applications in diverse areas ranging from material sciences to biology and neuroscience. Get Access to the Authors’ Own Cutting-Edge Open-Source Software Projects—and Then Actually Contribute to Them Yourself! The authors of Shape Analysis and Classification: Theory and Practice, Second Edition have improved the bestselling first edition by updating the tremendous progress in the field. This exceptionally accessible book presents the most advanced imaging techniques used for analyzing general biological shapes, such as those of cells, tissues, organs, and organisms. It implements numerous corrections and improvements—many of which were suggested by readers of the first edition—to optimize understanding and create what can truly be called an interactive learning experience. New Material in This Second Edition Addresses Graph and complex networks Dimensionality reduction Structural pattern recognition Shape representation using graphs Graphically reformulated, this edition updates equations, figures, and references, as well as slides that will be useful in related courses and general discussion. Like the popular first edition, this text is applicable to many fields and certain to become a favored addition to any library. Visit http://www.vision.ime.usp.br/~cesar/shape/ for Useful Software, Databases, and Videos

Introduction to Statistical Pattern Recognition

Introduction to Statistical Pattern Recognition PDF Author: Keinosuke Fukunaga
Publisher: Elsevier
ISBN: 0080478654
Category : Computers
Languages : en
Pages : 606

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Book Description
This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises.

Classification, Parameter Estimation and State Estimation

Classification, Parameter Estimation and State Estimation PDF Author: Ferdinand van der Heijden
Publisher: John Wiley & Sons
ISBN: 0470090146
Category : Science
Languages : en
Pages : 440

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Book Description
Classification, Parameter Estimation and State Estimation is a practical guide for data analysts and designers of measurement systems and postgraduates students that are interested in advanced measurement systems using MATLAB. 'Prtools' is a powerful MATLAB toolbox for pattern recognition and is written and owned by one of the co-authors, B. Duin of the Delft University of Technology. After an introductory chapter, the book provides the theoretical construction for classification, estimation and state estimation. The book also deals with the skills required to bring the theoretical concepts to practical systems, and how to evaluate these systems. Together with the many examples in the chapters, the book is accompanied by a MATLAB toolbox for pattern recognition and classification. The appendix provides the necessary documentation for this toolbox as well as an overview of the most useful functions from these toolboxes. With its integrated and unified approach to classification, parameter estimation and state estimation, this book is a suitable practical supplement in existing university courses in pattern classification, optimal estimation and data analysis. Covers all contemporary main methods for classification and estimation. Integrated approach to classification, parameter estimation and state estimation Highlights the practical deployment of theoretical issues. Provides a concise and practical approach supported by MATLAB toolbox. Offers exercises at the end of each chapter and numerous worked out examples. PRtools toolbox (MATLAB) and code of worked out examples available from the internet Many examples showing implementations in MATLAB Enables students to practice their skills using a MATLAB environment

Ecology and Classification of North American Freshwater Invertebrates

Ecology and Classification of North American Freshwater Invertebrates PDF Author: James H. Thorp
Publisher: Academic Press
ISBN: 0123748550
Category : Nature
Languages : en
Pages : 1036

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Book Description
"The third edition of Ecology and Classification of North American Freshwater Invertebrates continues the tradition of in-depth coverage of the biology, ecology, phylogeny, and identification of freshwater invertebrates from the USA and Canada. This text serves as an authoritative single source for a broad coverage of the anatomy, physiology, ecology, and phylogeny of all major groups of invertebrates in inland waters of North America, north of Mexico." --Book Jacket.

Classification Methods for Remotely Sensed Data

Classification Methods for Remotely Sensed Data PDF Author: Paul Mather
Publisher: CRC Press
ISBN: 9780203303566
Category : Technology & Engineering
Languages : en
Pages : 358

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Book Description
Remote sensing is an integral part of geography, GIS and cartography, used by academics in the field and professionals in all sorts of occupations. The 1990s saw the development of a range of new methods of classifying remote sensing images and data, both optical imaging and microwave imaging. This comprehensive survey of the various techniques pul

Image Analysis, Classification and Change Detection in Remote Sensing

Image Analysis, Classification and Change Detection in Remote Sensing PDF Author: Morton J. Canty
Publisher: CRC Press
ISBN: 1466570377
Category : Mathematics
Languages : en
Pages : 575

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Book Description
Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL and Python, Third Edition introduces techniques used in the processing of remote sensing digital imagery. It emphasizes the development and implementation of statistically motivated, data-driven techniques. The author achieves this by tightly interweaving theory, algorithms, and computer codes. See What’s New in the Third Edition: Inclusion of extensive code in Python, with a cloud computing example New material on synthetic aperture radar (SAR) data analysis New illustrations in all chapters Extended theoretical development The material is self-contained and illustrated with many programming examples in IDL. The illustrations and applications in the text can be plugged in to the ENVI system in a completely transparent fashion and used immediately both for study and for processing of real imagery. The inclusion of Python-coded versions of the main image analysis algorithms discussed make it accessible to students and teachers without expensive ENVI/IDL licenses. Furthermore, Python platforms can take advantage of new cloud services that essentially provide unlimited computational power. The book covers both multispectral and polarimetric radar image analysis techniques in a way that makes both the differences and parallels clear and emphasizes the importance of choosing appropriate statistical methods. Each chapter concludes with exercises, some of which are small programming projects, intended to illustrate or justify the foregoing development, making this self-contained text ideal for self-study or classroom use.