Pattern Recognition

Concepts, Methods and Applications
Author: J.P. Marques de Sá
Publisher: Springer Science & Business Media
ISBN: 3642566510
Category: Computers
Page: 318
View: 7063
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The book provides a comprehensive view of pattern recognition concepts and methods, illustrated with real-life applications in several areas. A CD-ROM offered with the book includes datasets and software tools, making it easier to follow in a hands-on fashion, right from the start.

Pattern Recognition


Author: Sergios Theodoridis,Konstantinos Koutroumbas
Publisher: Elsevier
ISBN: 9780080513614
Category: Computers
Page: 856
View: 9983
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Pattern recognition is a fast growing area with applications in a widely diverse number of fields such as communications engineering, bioinformatics, data mining, content-based database retrieval, to name but a few. This new edition addresses and keeps pace with the most recent advancements in these and related areas. This new edition: a) covers Data Mining, which was not treated in the previous edition, and is integrated with existing material in the book, b) includes new results on Learning Theory and Support Vector Machines, that are at the forefront of today's research, with a lot of interest both in academia and in applications-oriented communities, c) for the first time treats audio along with image applications since in today's world the most advanced applications are treated in a unified way and d) the subject of classifier combinations is treated, since this is a hot topic currently of interest in the pattern recognition community. * The latest results on support vector machines including v-SVM's and their geometric interpretation * Classifier combinations including the Boosting approach * State-of-the-art material for clustering algorithms tailored for large data sets and/or high dimensional data, as required by applications such as web-mining and bioinformatics * Coverage of diverse applications such as image analysis, optical character recognition, channel equalization, speech recognition and audio classification

Pattern Recognition


Author: Konstantinos Koutroumbas,Sergios Theodoridis
Publisher: Academic Press
ISBN: 9780080949123
Category: Computers
Page: 984
View: 500
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This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition: semi-supervised learning, combining clustering algorithms, and relevance feedback. · Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques · Many more diagrams included--now in two color--to provide greater insight through visual presentation · Matlab code of the most common methods are given at the end of each chapter. · More Matlab code is available, together with an accompanying manual, via this site · Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms. · An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary, and solved examples including real-life data sets in imaging, and audio recognition. The companion book will be available separately or at a special packaged price (ISBN: 9780123744869). Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques Many more diagrams included--now in two color--to provide greater insight through visual presentation Matlab code of the most common methods are given at the end of each chapter An accompanying book with 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. The companion book is available separately or at a special packaged price (Book ISBN: 9780123744869. Package ISBN: 9780123744913) Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms Solutions manual, powerpoint slides, and additional resources are available to faculty using the text for their course. Register at www.textbooks.elsevier.com and search on "Theodoridis" to access resources for instructor.

Pattern Recognition in Biology


Author: Marsha S. Corrigan
Publisher: Nova Publishers
ISBN: 9781600217166
Category: Science
Page: 253
View: 2652
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Pattern recognition is the research area that studies the operation and design of systems that recognise patterns in data. It encloses subdisciplines like discriminant analysis, feature extraction, error estimation, cluster analysis, grammatical inference and parsing. This book presents research from around the world.

Pattern Recognition

From Classical to Modern Approaches
Author: Sankar K. Pal,Pal. Amita
Publisher: World Scientific
ISBN: 9789812386533
Category: Computers
Page: 612
View: 1968
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This volume, containing contributions by experts from all over the world, is a collection of 21 articles which present review and research material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, syntactic/linguistic, fuzzy-set-theoretic, neural, genetic-algorithmic and rough-set-theoretic to hybrid soft computing, with significant real-life applications. In addition, the book describes efficient soft machine learning algorithms for data mining and knowledge discovery. With a balanced mixture of theory, algorithms and applications, as well as up-to-date information and an extensive bibliography, Pattern Recognition: From Classical to Modern Approaches is a very useful resource. Contents: Pattern Recognition: Evolution of Methodologies and Data Mining (A Pal & S K Pal); Adaptive Stochastic Algorithms for Pattern Classification (M A L Thathachar & P S Sastry); Shape in Images (K V Mardia); Decision Trees for Classification: A Review and Some New Results (R Kothari & M Dong); Syntactic Pattern Recognition (A K Majumder & A K Ray); Fuzzy Sets as a Logic Canvas for Pattern Recognition (W Pedrycz & N Pizzi); Neural Network Based Pattern Recognition (V David Sanchez A); Networks of Spiking Neurons in Data Mining (K Cios & D M Sala); Genetic Algorithms, Pattern Classification and Neural Networks Design (S Bandyopadhyay et al.); Rough Sets in Pattern Recognition (A Skowron & R Swiniarski); Automated Generation of Qualitative Representations of Complex Objects by Hybrid Soft-Computing Methods (E H Ruspini & I S Zwir); Writing Speed and Writing Sequence Invariant On-line Handwriting Recognition (S-H Cha & S N Srihari); Tongue Diagnosis Based on Biometric Pattern Recognition Technology (K Wang et al.); and other papers. Readership: Graduate students, researchers and academics in pattern recognition.

Pattern Recognition and Classification in Time Series Data


Author: Volna, Eva,Kotyrba, Martin,Janosek, Michal
Publisher: IGI Global
ISBN: 1522505660
Category: Computers
Page: 282
View: 7743
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Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.

Pattern Recognition

An introduction
Author: Brett Anderson
Publisher: Scientific e-Resources
ISBN: 1839472391
Category:
Page: N.A
View: 9476
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Watching the environment and recognising patterns with the end goal of basic leadership is central to human instinct. This book manages the logical train that empowers comparable observation in machines through pattern recognition, which has application in differing innovation regions-character recognition, picture handling, modern computerization, web looks, discourse recognition, therapeutic diagnostics, target recognition, space science, remote detecting, information mining, biometric recognizable proof-to give some examples. This book is a composition of central subjects in pattern recognition utilizing an algorithmic approach. It gives a careful prologue to the ideas of pattern recognition and an efficient record of the real points in pattern recognition other than assessing the huge advance made in the field as of late. It incorporates fundamental strategies of pattern recognition, neural systems, bolster vector machines and choice trees. While hypothetical angles have been given due scope, the accentuation is more on the pragmatic. Pattern recognition has application in practically every field of human undertaking including topography, geology, space science and brain research. All the more particularly, it is helpful in bioinformatics, mental investigation, biometrics and a large group of different applications.

Statistical Pattern Recognition


Author: Andrew R. Webb
Publisher: John Wiley & Sons
ISBN: 0470854782
Category: Mathematics
Page: 514
View: 3155
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Statistical pattern recognition is a very active area of study and research, which has seen many advances in recent years. New and emerging applications - such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition - require robust and efficient pattern recognition techniques. Statistical decision making and estimation are regarded as fundamental to the study of pattern recognition. Statistical Pattern Recognition, Second Edition has been fully updated with new methods, applications and references. It provides a comprehensive introduction to this vibrant area - with material drawn from engineering, statistics, computer science and the social sciences - and covers many application areas, such as database design, artificial neural networks, and decision support systems. * Provides a self-contained introduction to statistical pattern recognition. * Each technique described is illustrated by real examples. * Covers Bayesian methods, neural networks, support vector machines, and unsupervised classification. * Each section concludes with a description of the applications that have been addressed and with further developments of the theory. * Includes background material on dissimilarity, parameter estimation, data, linear algebra and probability. * Features a variety of exercises, from 'open-book' questions to more lengthy projects. The book is aimed primarily at senior undergraduate and graduate students studying statistical pattern recognition, pattern processing, neural networks, and data mining, in both statistics and engineering departments. It is also an excellent source of reference for technical professionals working in advanced information development environments.

Introduction to Statistical Pattern Recognition


Author: Keinosuke Fukunaga
Publisher: Elsevier
ISBN: 9780080478654
Category: Computers
Page: 592
View: 1155
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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.

VLSI for Pattern Recognition and Image Processing


Author: K.S. Fu
Publisher: Springer Science & Business Media
ISBN: 364247523X
Category: Technology & Engineering
Page: 236
View: 7174
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During the past two decades there has been a considerable growth in interest in problems of pattern recognition and image processing (PRIP). This inter est has created an increasing need for methods and techniques for the design of PRIP systems. PRIP involves analysis, classification and interpretation of data. Practical applications of PRIP include character recognition, re mote sensing, analysis of medical signals and images, fingerprint and face identification, target recognition and speech understanding. One difficulty in making PRIP systems practically feasible, and hence, more popularly used, is the requirement of computer time and storage. This situation is particularly serious when the patterns to be analyzed are quite complex. Thus it is of the utmost importance to investigate special comput er architectures and their implementations for PRIP. Since the advent of VLSI technology, it is possible to put thousands of components on one chip. This reduces the cost of processors and increases the processing speed. VLSI algorithms and their implementations have been recently developed for PRIP. This book is intended to document the recent major progress in VLSI system design for PRIP applications.

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

23rd Iberoamerican Congress, CIARP 2018, Madrid, Spain, November 19-22, 2018, Proceedings
Author: Ruben Vera-Rodriguez,Julian Fierrez,Aythami Morales
Publisher: Springer
ISBN: 3030134695
Category: Computers
Page: 987
View: 8434
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This book constitutes the refereed post-conference proceedings of the 23rd Iberoamerican Congress on Pattern Recognition, CIARP 2018, held in Madrid, Spain, in November 2018 The 112 papers presented were carefully reviewed and selected from 187 submissions The program was comprised of 6 oral sessions on the following topics: machine learning, computer vision, classification, biometrics and medical applications, and brain signals, and also on: text and character analysis, human interaction, and sentiment analysis

Pattern Recognition

An Algorithmic Approach
Author: M. Narasimha Murty,V. Susheela Devi
Publisher: Springer Science & Business Media
ISBN: 9780857294951
Category: Computers
Page: 263
View: 8370
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Observing the environment and recognising patterns for the purpose of decision making is fundamental to human nature. This book deals with the scientific discipline that enables similar perception in machines through pattern recognition (PR), which has application in diverse technology areas. This book is an exposition of principal topics in PR using an algorithmic approach. It provides a thorough introduction to the concepts of PR and a systematic account of the major topics in PR besides reviewing the vast progress made in the field in recent times. It includes basic techniques of PR, neural networks, support vector machines and decision trees. While theoretical aspects have been given due coverage, the emphasis is more on the practical. The book is replete with examples and illustrations and includes chapter-end exercises. It is designed to meet the needs of senior undergraduate and postgraduate students of computer science and allied disciplines.

Pattern Recognition


Author: William Gibson
Publisher: Penguin UK
ISBN: 0141904461
Category: Fiction
Page: 368
View: 3901
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Pattern Recognition - a pulsating techno-thriller by William Gibson, bestselling author of Neuromancer Cayce Pollard has been flown to London. She's a 'coolhunter' - her services for hire to global corporations desperate for certainty in a capricious and uncertain world. Now she's been offered a special project: track down the makers of the addictive online film that's lighting up the 'net. Hunting the source will take her to Tokyo and Moscow and put her in the sights of Japanese computer crazies and Russian Mafia men. She's up against those who want to control the film, to own it - who figure breaking the law is just another business strategy. The kind of people who relish turning the hunter into the hunted . . . William Gibson is a prophet and a satirist, a black comedian and an outstanding architect of cool. Readers of Neal Stephenson, Ray Bradbury and Iain M. Banks will love this book. Pattern Recognition is the first novel in the Blue Ant trilogy - read Spook Country and Zero History for more. 'A big novel, full of bold ideas . . . races along like an expert thriller' GQ 'Dangerously hip. Its dialogue and characterization will amaze you. A wonderfully detailed, reckless journey of espionage and lies' USA Today 'A compelling, humane story with a sympathetic heroine searching for meaning and consolation in a post-everything world' Daily Telegraph Idoru is a gripping techno-thriller by William Gibson, bestselling author of Neuromancer 'Fast, witty and cleverly politicized' Guardian

Pattern Recognition

A Statistical Approach
Author: Pierre A. Devyver,Josef (1946- ) Kittler
Publisher: Prentice Hall
ISBN: 9780136542360
Category: Computers
Page: 448
View: 3858
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Pattern Recognition and Neural Networks


Author: Brian D. Ripley
Publisher: Cambridge University Press
ISBN: 9780521717700
Category: Computers
Page: 403
View: 5544
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Ripley brings together two crucial ideas in pattern recognition: statistical methods and machine learning via neural networks. He brings unifying principles to the fore, and reviews the state of the subject. Ripley also includes many examples to illustrate real problems in pattern recognition and how to overcome them.

Pattern Recognition and Image Preprocessing


Author: Sing T. Bow
Publisher: CRC Press
ISBN: 9780203903896
Category: Technology & Engineering
Page: 720
View: 4617
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Describing non-parametric and parametric theoretic classification and the training of discriminant functions, this second edition includes new and expanded sections on neural networks, Fisher's discriminant, wavelet transform, and the method of principal components. It contains discussions on dimensionality reduction and feature selection; novel computer system architectures; proven algorithms for solutions to common roadblocks in data processing; computing models including the Hamming net, the Kohonen self-organizing map, and the Hopfield net; detailed appendices with data sets illustrating key concepts in the text; and more.

Image Processing and Pattern Recognition

Fundamentals and Techniques
Author: Frank Y. Shih
Publisher: John Wiley & Sons
ISBN: 9780470590409
Category: Technology & Engineering
Page: 552
View: 6430
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A comprehensive guide to the essential principles of image processing and pattern recognition Techniques and applications in the areas of image processing and pattern recognition are growing at an unprecedented rate. Containing the latest state-of-the-art developments in the field, Image Processing and Pattern Recognition presents clear explanations of the fundamentals as well as the most recent applications. It explains the essential principles so readers will not only be able to easily implement the algorithms and techniques, but also lead themselves to discover new problems and applications. Unlike other books on the subject, this volume presents numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. Scores of graphs and examples, technical assistance, and practical tools illustrate the basic principles and help simplify the problems, allowing students as well as professionals to easily grasp even complicated theories. It also features unique coverage of the most interesting developments and updated techniques, such as image watermarking, digital steganography, document processing and classification, solar image processing and event classification, 3-D Euclidean distance transformation, shortest path planning, soft morphology, recursive morphology, regulated morphology, and sweep morphology. Additional topics include enhancement and segmentation techniques, active learning, feature extraction, neural networks, and fuzzy logic. Featuring supplemental materials for instructors and students, Image Processing and Pattern Recognition is designed for undergraduate seniors and graduate students, engineering and scientific researchers, and professionals who work in signal processing, image processing, pattern recognition, information security, document processing, multimedia systems, and solar physics.

Attention and Pattern Recognition


Author: Nick Lund
Publisher: Psychology Press
ISBN: 9780415233095
Category: Psychology
Page: 129
View: 3696
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Introduces the main psychological research on attention and the methods that have been used to study it.

A Probabilistic Theory of Pattern Recognition


Author: Luc Devroye,Laszlo Györfi,Gabor Lugosi
Publisher: Springer Science & Business Media
ISBN: 1461207118
Category: Mathematics
Page: 638
View: 4085
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A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field.