Hybrid Intelligent Techniques for Pattern Analysis and Understanding

Hybrid Intelligent Techniques for Pattern Analysis and Understanding
Author: Siddhartha Bhattacharyya
Publisher: CRC Press
Total Pages: 393
Release: 2017-10-30
Genre: Computers
ISBN: 1498769373

Hybrid Intelligent Techniques for Pattern Analysis and Understanding outlines the latest research on the development and application of synergistic approaches to pattern analysis in real-world scenarios. An invaluable resource for lecturers, researchers, and graduates students in computer science and engineering, this book covers a diverse range of hybrid intelligent techniques, including image segmentation, character recognition, human behavioral analysis, hyperspectral data processing, and medical image analysis.

Pattern Analysis

Pattern Analysis
Author: H. Niemann
Publisher: Springer Science & Business Media
Total Pages: 316
Release: 2012-12-06
Genre: Computers
ISBN: 3642966500

This book is devoted to pattern analysis, that is, the automatic construc tion of a symbolic description for a complex pattern, like an image or con nected speech. Pattern analysis thus tries to simulate certain capabilities which go without saying in any human central nervous system. The increasing interest and growing efforts at solving the problems related with pattern analysis are motivated by the challenge of the problem and the expected ap plications. Potential applications are numerous and result from the fact that data can be gathered and stored by modern devices in ever increasing extent, thus making the finding of particular interesting facts or events in these hosts of data an ever increasing problem. It was tried to organize the book around one particular view of pattern analysis: the view that pattern analysis requires an appropriate set of modules operating on a common data base which contains interme processing diate results of processing. Although other views are certainly possible, this one was adopted because the author feels that it is a useful idea, be cause the size of this book had to be kept within reasonable bounds, and because it facilitated the composition of fairly self-contained chapters.

Analysis Patterns

Analysis Patterns
Author: Martin Fowler
Publisher: Addison-Wesley Professional
Total Pages: 398
Release: 1997
Genre: Object-oriented methods (Computer science).
ISBN: 9780201895421

Martin Fowler is a consultant specializing in object-oriented analysis and design. This book presents and discusses a number of object models derived from various problem domains. All patterns and models presented have been derived from the author's own consulting work and are based on real business cases.

Pattern Analysis and Understanding

Pattern Analysis and Understanding
Author: Heinrich Niemann
Publisher: Springer Science & Business Media
Total Pages: 384
Release: 2013-04-17
Genre: Science
ISBN: 3642748996

In this second edition every chapter of the first edition of Pattern Analysis has been updated and expanded. The general view of a system for pattern analysis and understanding has remained unchanged, but many details have been revised. A short account of light and sound has been added to the introduction, some normalization techniques and a basic introduction to morphological operations have been added to the second chapter. Chapter 3 has been expanded significantly by topics like motion, depth, and shape from shading; additional material has also been added to the already existing sections of this chapter. The old sections of Chap. 4 have been reorganized, a general view of the classification problem has been added and material provided to incorporate techniques of word and object recognition and to give a short account of some types of neural nets. Almost no changes have been made in Chap. 5. The part on representation of control structures in Chap. 6 has been shortened, a section on the judgement of results has been added. Chapter 7 has been rewritten almost completely; the section on formal grammars has been reduced, the sections on production systems, semantic networks, and knowledge acquisition have been expanded, and sections on logic and explanation added. The old Chaps. 8 and 9 have been omitted. In summary, the new edition is a thorough revision and extensive update of the first one taking into account the progress in the field during recent years.

Handbook Of Pattern Recognition And Computer Vision (2nd Edition)

Handbook Of Pattern Recognition And Computer Vision (2nd Edition)
Author: Chi Hau Chen
Publisher: World Scientific
Total Pages: 1045
Release: 1999-03-12
Genre: Computers
ISBN: 9814497649

The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.

Advantages and Pitfalls of Pattern Recognition

Advantages and Pitfalls of Pattern Recognition
Author: Horst Langer
Publisher: Elsevier
Total Pages: 352
Release: 2019-11-23
Genre: Science
ISBN: 0128118431

Advantages and Pitfalls of Pattern Recognition presents various methods of pattern recognition and classification, useful to geophysicists, geochemists, geologists, geographers, data analysts, and educators and students of geosciences. Scientific and technological progress has dramatically improved the knowledge of our planet with huge amounts of digital data available in various fields of Earth Sciences, such as geology, geophysics, and geography. This has led to a new perspective of data analysis, requiring specific techniques that take several features into consideration rather than single parameters. Pattern recognition techniques offer a suitable key for processing and extracting useful information from the data of multivariate analysis. This book explores both supervised and unsupervised pattern recognition techniques, while providing insight into their application. - Offers real-world examples of techniques for pattern recognition and handling multivariate data - Includes examples, applications, and diagrams to enhance understanding - Provides an introduction and access to relevant software packages

Solving Data Mining Problems Through Pattern Recognition

Solving Data Mining Problems Through Pattern Recognition
Author: Ruby L. Kennedy
Publisher: Prentice Hall
Total Pages: 424
Release: 1997
Genre: Computers
ISBN:

Data mining is an exploding technology increasingly used in major industries like finance, aerospace, and the medical industry. To truly take advantage of data mining capabilities, one must use and understand pattern recognition techniques. They are addressed in this book along with a tutorial on how to use the accompanying pattern software ("Pattern Recognition Workbench") on the CD-ROM.

Essentials of Pattern Recognition

Essentials of Pattern Recognition
Author: Jianxin Wu
Publisher: Cambridge University Press
Total Pages: 401
Release: 2020-11-19
Genre: Computers
ISBN: 1108483461

An accessible undergraduate introduction to the concepts and methods in pattern recognition, machine learning and deep learning.

Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning
Author: Christopher M. Bishop
Publisher: Springer
Total Pages: 0
Release: 2016-08-23
Genre: Computers
ISBN: 9781493938438

This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.