Introduction to Pattern Recognition

A Matlab Approach
Author: Sergios Theodoridis,Aggelos Pikrakis,Konstantinos Koutroumbas,Dionisis Cavouras
Publisher: Academic Press
ISBN: 9780080922751
Category: Computers
Page: 231
View: 4855

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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)

Handbook of Pattern Recognition and Computer Vision


Author: Chi-hau Chen
Publisher: World Scientific
ISBN: 9814273392
Category: Computers
Page: 796
View: 5399

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Both pattern recognition and computer vision have experienced rapid progress in the last twenty-five years. This book provides the latest advances on pattern recognition and computer vision along with their many applications. It features articles written by renowned leaders in the field while topics are presented in readable form to a wide range of readers. The book is divided into five parts: basic methods in pattern recognition, basic methods in computer vision and image processing, recognition applications, life science and human identification, and systems and technology.

Pattern Recognition


Author: Sergios Theodoridis,Konstantinos Koutroumbas
Publisher: Academic Press
ISBN: 9780080949123
Category: Computers
Page: 984
View: 569

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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.

Machine Learning and Data Mining in Pattern Recognition

4th International Conference, MLDM 2005, Leipzig, Germany, July 9-11, 2005, Proceedings
Author: Petra Perner,Atsushi Imiya
Publisher: Springer Science & Business Media
ISBN: 3540269231
Category: Computers
Page: 698
View: 5578

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We met again in front of the statue of Gottfried Wilhelm von Leibniz in the city of Leipzig. Leibniz, a famous son of Leipzig, planned automatic logical inference using symbolic computation, aimed to collate all human knowledge. Today, artificial intelligence deals with large amounts of data and knowledge and finds new information using machine learning and data mining. Machine learning and data mining are irreplaceable subjects and tools for the theory of pattern recognition and in applications of pattern recognition such as bioinformatics and data retrieval. This was the fourth edition of MLDM in Pattern Recognition which is the main event of Technical Committee 17 of the International Association for Pattern Recognition; it started out as a workshop and continued as a conference in 2003. Today, there are many international meetings which are titled “machine learning” and “data mining”, whose topics are text mining, knowledge discovery, and applications. This meeting from the first focused on aspects of machine learning and data mining in pattern recognition problems. We planned to reorganize classical and well-established pattern recognition paradigms from the viewpoints of machine learning and data mining. Though it was a challenging program in the late 1990s, the idea has inspired new starting points in pattern recognition and effects in other areas such as cognitive computer vision.

Applied Pattern Recognition

Algorithms and Implementation in C++
Author: Dietrich Paulus,Joachim Hornegger
Publisher: Springer Science & Business Media
ISBN: 9783528355586
Category: Technology & Engineering
Page: 372
View: 3882

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This book demonstrates the efficiency of the C++ programming language in the realm of pattern recognition and pattern analysis. For this 4th edition, new features of the C++ language were integrated and their relevance for image and speech processing is discussed.

Pattern Recognition in Bioinformatics

4th IAPR International Conference, PRIB 2009, Sheffield, UK, September 7-9, 2009, Proceedings
Author: Visakan Kadirkamanathan,Guido Sanguinetti,Mark Girolami,Mahesan Niranjan,Josselin Noirel
Publisher: Springer
ISBN: 3642040314
Category: Science
Page: 452
View: 4236

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This book constitutes the refereed proceedings of the Fourth International Workshop on Pattern Recognition in Bioinformatics, PRIB 2009, held in Sheffield, UK, in September 2009. The 38 revised full papers presented were carefully reviewed and selected from numerous submissions. The topics covered by these papers range from image analysis for biomedical data to systems biology. The conference aims at crating a focus for the development and application of pattern recognition techniques in the biological domain.

NEURAL NETWORKS AND PATTERN RECOGNITION. Edition en anglais


Author: Omid Omidvar,Judith E. Dayhoff
Publisher: Academic Press
ISBN: 9780125264204
Category: Computers
Page: 351
View: 4336

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Pulse-coupled neural networks; A neural network model for optical flow computation; Temporal pattern matching using an artificial neural network; Patterns of dynamic activity and timing in neural network processing; A macroscopic model of oscillation in ensembles of inhibitory and excitatory neurons; Finite state machines and recurrent neural networks: automata and dynamical systems approaches; biased random-waldk learning; a neurobiological correlate to trial-and-error; Using SONNET 1 to segment continuous sequences of items; On the use of high-level petri nets in the modeling of biological neural networks; Locally recurrent networks: the gmma operator, properties, and extensions.

Maschinelles Lernen


Author: Ethem Alpaydin
Publisher: De Gruyter Oldenbourg
ISBN: 9783486581140
Category: Machine learning
Page: 440
View: 4629

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Maschinelles Lernen heißt, Computer so zu programmieren, dass ein bestimmtes Leistungskriterium anhand von Beispieldaten und Erfahrungswerten aus der Vergangenheit optimiert wird. Das vorliegende Buch diskutiert diverse Methoden, die ihre Grundlagen in verschiedenen Themenfeldern haben: Statistik, Mustererkennung, neuronale Netze, Künstliche Intelligenz, Signalverarbeitung, Steuerung und Data Mining. In der Vergangenheit verfolgten Forscher verschiedene Wege mit unterschiedlichen Schwerpunkten. Das Anliegen dieses Buches ist es, all diese unterschiedlichen Ansätze zu kombinieren, um eine allumfassende Behandlung der Probleme und ihrer vorgeschlagenen Lösungen zu geben.

Graph Based Representations in Pattern Recognition

4th IAPR International Workshop, GbRPR 2003, York, UK, June 30 - July 2, 2003. Proceedings
Author: Edwin Hancock,Mario Vento
Publisher: Springer
ISBN: 3540450289
Category: Computers
Page: 276
View: 822

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The refereed proceedings of the 4th IAPR International Workshop on Graph-Based Representation in Pattern Recognition, GbRPR 2003, held in York, UK in June/July 2003. The 23 revised full papers presented were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on data structures and representation, segmentation, graph edit distance, graph matching, matrix methods, and graph clustering.

Data mining

praktische Werkzeuge und Techniken für das maschinelle Lernen
Author: Ian H. Witten,Eibe Frank
Publisher: N.A
ISBN: 9783446215337
Category:
Page: 386
View: 5404

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Chirurgie der Kleintiere


Author: Theresa Welch Fossum
Publisher: Elsevier,Urban&FischerVerlag
ISBN: 3437597582
Category: Medical
Page: 1656
View: 4307

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Unentbehrlich für den chirurgischen Alltag! Ob zum Nachschlagen oder zum schnellen Abklären aktueller Probleme - "Fossum" lässt keine Fragen offen. Über 1.500 farbige Abbildungen verdeutlichen die Inhalte. Neu in der 2. Auflage • Neue Kapitel: physikalische Therapie, minimalinvasive Verfahren, Operationen des Auges • Deutlich erweitert:Perioperative multimodale Schmerztherapie, Arthroskopie, Ellenbogendysplasie beim Hund, Gelenkersatz und die Behandlung von Osteoarthritis • Mehr über die neuesten bildgebenden Verfahren

Pattern Recognition Neuroradiology


Author: Neil M. Borden,Scott E. Forseen
Publisher: Cambridge University Press
ISBN: 1139502247
Category: Medical
Page: N.A
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Faced with a single neuroradiological image of an unknown patient, how confident would you be to make a differential diagnosis? Despite advanced imaging techniques, a confident diagnosis also requires knowledge of the patient's age, clinical data and the lesion location. Pattern Recognition Neuroradiology provides the tools you will need to arrive at the correct diagnosis or a reasonable differential diagnosis. This user-friendly book includes basic information often omitted from other texts: a practical method of image analysis, sample dictation templates and didactic information regarding lesions/diseases in a concise outline form. Image galleries show more than 700 high quality representative examples of the diseases discussed. Whether you are a trainee encountering some of these conditions for the first time or a resident trying to develop a reliable system of image analysis, Pattern Recognition Neuroradiology is an invaluable diagnostic resource.

Entwurfsmuster

Elemente wiederverwendbarer objektorientierter Software
Author: N.A
Publisher: Pearson Deutschland GmbH
ISBN: 9783827328243
Category:
Page: 479
View: 6212

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Discriminant analysis and statistical pattern recognition


Author: Geoffrey J. McLachlan
Publisher: Wiley-Interscience
ISBN: 9780471615316
Category: Mathematics
Page: 526
View: 9431

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The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "For both applied and theoretical statisticians as well as investigators working in the many areas in which relevant use can be made of discriminant techniques, this monograph provides a modern, comprehensive, and systematic account of discriminant analysis, with the focus on the more recent advances in the field." -SciTech Book News ". . . a very useful source of information for any researcher working in discriminant analysis and pattern recognition." -Computational Statistics Discriminant Analysis and Statistical Pattern Recognition provides a systematic account of the subject. While the focus is on practical considerations, both theoretical and practical issues are explored. Among the advances covered are regularized discriminant analysis and bootstrap-based assessment of the performance of a sample-based discriminant rule, and extensions of discriminant analysis motivated by problems in statistical image analysis. The accompanying bibliography contains over 1,200 references.

Lineare Algebra

Einführung, Grundlagen, Übungen
Author: Howard Anton
Publisher: Springer Verlag
ISBN: 9783827403247
Category: Mathematics
Page: 680
View: 9575

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In Ihrer Hand liegt ein Lehrbuch - in sieben englischsprachigen Ausgaben praktisch erprobt - das Sie mit groem didaktischen Geschick, zudem angereichert mit zahlreichen Ubungsaufgaben, in die Grundlagen der linearen Algebra einfuhrt. Kenntnisse der Analysis werden fur das Verstandnis nicht generell vorausgesetzt, sind jedoch fur einige besonders gekennzeichnete Beispiele notig. Padagogisch erfahren, behandelt der Autor grundlegende Beweise im laufenden Text; fur den interessierten Leser jedoch unverzichtbare Beweise finden sich am Ende der entsprechenden Kapitel. Ein weiterer Vorzug des Buches: Die Darstellung der Zusammenhange zwischen den einzelnen Stoffgebieten - linearen Gleichungssystemen, Matrizen, Determinanten, Vektoren, linearen Transformationen und Eigenwerten.

Statistical pattern recognition


Author: Andrew R. Webb
Publisher: John Wiley & Sons Inc
ISBN: N.A
Category: Business & Economics
Page: 496
View: 6905

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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. For further information on the techniques and applications discussed in this book please visit www.statistical-pattern-recognition.net