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: 742

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)
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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

ISBN: 3540318917

Category: Computers

Page: 698

View: 8925

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.
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Pattern Recognition

Author: Sergios Theodoridis,Konstantinos Koutroumbas

Publisher: Academic Press

ISBN: 9780080949123

Category: Computers

Page: 984

View: 3808

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.
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Mustererkennung im Mittelspiel

Schärfen Sie Ihren Blick für Schlüsselzüge im Schach

Author: International Master Arthur van de Oudeweetering

Publisher: New In Chess

ISBN: 9056916165

Category: Games

Page: 304

View: 1966

Die Mustererkennung ist eines der wichtigsten Werkzeuge bei der Verbesserung im Schach. Die Erkenntnis, dass die Stellung auf dem Brett Ähnlichkeiten mit etwas hat, was man bereits gesehen hat, erleichtert Ihnen, rasch den Gehalt der Stellung zu erfassen und die vielversprechendste Fortsetzung zu finden. Mustererkennung im Mittelspiel versorgt Sie mit einem reichhaltigen Schatz an wichtigen und doch leicht einzuprägenden Bausteinen für Ihr Schachwissen. In 40 kurzen, scharf umrissenen Kapiteln präsentiert der erfahrene Schachtrainer Arthur van de Oudeweetering hunderte Beispiele zu verblüffenden Mittelspielthemen. Um Ihr Verständnis zu testen, gibt es zu jedem Abschnitt Aufgaben. Nach der Arbeit mit diesem Buch wird sich Ihr Schachwissen ganz wie von selbst um die Kenntnis zahlreicher Stellungstypen, Bauernstrukturen und Figurenkonstellationen vermehrt haben. Im Ergebnis werden Sie den richtigen Zug häufiger und auch rascher finden!
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Pattern Recognition and Image Analysis

4th Iberian Conference, IbPRIA 2009 Póvoa de Varzim, Portugal, June 10-12, 2009 Proceedings

Author: Hélder J. Araújo,Ana Maria Mendonça,Armando J. Pinho

Publisher: Springer Science & Business Media

ISBN: 3642021719

Category: Computers

Page: 514

View: 9972

This volume constitutes the refereed proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2009, held in Póvoa de Varzim, Portugal in June 2009. The 33 revised full papers and 29 revised poster papers presented together with 3 invited talks were carefully reviewed and selected from 106 submissions. The papers are organized in topical sections on computer vision, image analysis and processing, as well as pattern recognition.
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Handbook of Pattern Recognition and Computer Vision (5th Edition)

Author: Chi-hau Chen

Publisher: World Scientific

ISBN: 9814656534

Category: Computers

Page: 584

View: 3910

The book provides an up-to-date and authoritative treatment of pattern recognition and computer vision, with chapters written by leaders in the field. On the basic methods in pattern recognition and computer vision, topics range from statistical pattern recognition to array grammars to projective geometry to skeletonization, and shape and texture measures. Recognition applications include character recognition and document analysis, detection of digital mammograms, remote sensing image fusion, and analysis of functional magnetic resonance imaging data, etc.
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Applied Pattern Recognition

Algorithms and Implementation in C++

Author: Dietrich W. R. Paulus,Joachim Hornegger

Publisher: Springer Science & Business Media

ISBN: 9783528355586

Category: Computers

Page: 372

View: 7726

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.
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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: 3701

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Entwurfsmuster

Elemente wiederverwendbarer objektorientierter Software

Author: Erich Gamma,Ralph Johnson,Richard Helm,John Vlissides

Publisher: Pearson Deutschland GmbH

ISBN: 9783827330437

Category: Agile software development

Page: 479

View: 8597

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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,International Association for Pattern Recognition

Publisher: Springer Science & Business Media

ISBN: 354040452X

Category: Computers

Page: 270

View: 5367

This volume contains the papers presented at the Fourth IAPR Workshop on Graph Based Representations in Pattern Recognition. The workshop was held at the King’s Manor in York, England between 30 June and 2nd July 2003. The previous workshops in the series were held in Lyon, France (1997), Haindorf, Austria (1999), and Ischia, Italy (2001). The city of York provided an interesting venue for the meeting. It has been said that the history of York is the history of England. There have been both Roman and Viking episodes. For instance, Constantine was proclaimed emperor in York. The city has also been a major seat of ecclesiastical power and was also involved in the development of the railways in the nineteenth century. Much of York’s history is evidenced by its buildings, and the King’s Manor is one of the most important and attractive of these. Originally part of the Abbey, after the dissolution of the monasteries by Henry VIII, the building became a center of government for the Tudors and the Stuarts (who stayed here regularly on their journeys between London and Edinburgh), serving as the headquarters of the Council of the North until it was disbanded in 1561. The building became part of the University of York at its foundation in 1963. The papers in the workshop span the topics of representation, segmentation, graph-matching, graph edit-distance, matrix and spectral methods, and gra- clustering.
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Pattern Recognition

An Algorithmic Approach

Author: M. Narasimha Murty,V. Susheela Devi

Publisher: Springer Science & Business Media

ISBN: 9780857294951

Category: Computers

Page: 263

View: 1615

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.
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Artificial Neural Networks in Pattern Recognition

4th IAPR TC3 Workshop, ANNPR 2010, Cairo, Egypt, April 11-13, 2010, Proceedings

Author: Friedhelm Schwenker,Neamat El Gayar

Publisher: Springer

ISBN: 3642121594

Category: Computers

Page: 280

View: 6818

Artificial Neural Networks in Pattern Recognition synthesizes the proceedings of the 4th IAPR TC3 Workshop, ANNPR 2010. Topics include supervised and unsupervised learning, feature selection, pattern recognition in signal and image processing.
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UML 2 und Patterns angewendet - objektorientierte Softwareentwicklung

Author: Craig Larman

Publisher: mitp Verlags GmbH & Co. KG

ISBN: 9783826614538

Category:

Page: 716

View: 5711

Dieses Lehrbuch des international bekannten Autors und Software-Entwicklers Craig Larman ist ein Standardwerk zur objektorientierten Analyse und Design unter Verwendung von UML 2.0 und Patterns. Das Buch zeichnet sich insbesondere durch die Fahigkeit des Autors aus, komplexe Sachverhalte anschaulich und praxisnah darzustellen. Es vermittelt grundlegende OOA/D-Fertigkeiten und bietet umfassende Erlauterungen zur iterativen Entwicklung und zum Unified Process (UP). Anschliessend werden zwei Fallstudien vorgestellt, anhand derer die einzelnen Analyse- und Designprozesse des UP in Form einer Inception-, Elaboration- und Construction-Phase durchgespielt werden
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NEURAL NETWORKS AND PATTERN RECOGNITION. Edition en anglais

Author: Omid Omidvar,Judith E. Dayhoff

Publisher: Academic Press

ISBN: 9780125264204

Category: Computers

Page: 351

View: 4509

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.
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Smart Data Analytics

Mit Hilfe von Big Data Zusammenhänge erkennen und Potentiale nutzen

Author: Andreas Wierse,Till Riedel

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 3110461919

Category: Technology & Engineering

Page: 440

View: 3171

Wenn in Datenbergen wertvolle Geheimnisse schlummern, aus denen Profit erzielt werden soll, dann geht es um Big Data. Doch wie schöpft man aus »großen Daten« echte Werte, wenn man nicht gerade Google ist? Um aus Unternehmens-, Maschinen- oder Sensordaten einen Ertrag zu erzielen, reicht Big Data-Technologie allein nicht aus. Entscheidend sind die übergeordneten Innovations prozesse: die smarte Analyse von Big Data. Erst durch den kompetenten Einsatz der richtigen Werkzeuge und Techniken werden aus Big Data tatsächlich Smart Data. Das Praxishandbuch Smart Data Analytics gibt einen Überblick über die Technologie, die bei der Analyse von großen und heterogenen Datenmengen – inklusive Echtzeitdaten – zum Einsatz kommt. Elf Praxisbeispiele zeigen die konkrete Anwendung in kleinen und mittelständischen Unternehmen. So erfahren Sie, wie Sie Ihr Smart Data Analytics-Projekt in Ihrem eigenen Unternehmen vorbereiten und umsetzen können. Das Buch erläutert neben den organisatorischen Aspekten auch die rechtlichen Rahmenbedingungen. Und es zeigt, wie Sie sowohl den Nutzen bewerten können, der aus den Daten gezogen werden soll, als auch den Aufwand, den Sie dafür betreiben müssen. Denn Smart Data steht für mehr als nur die Untersuchung großer Datenmengen: Smart Data Analytics ist der Schlüssel zu einem smarten Umgang mit Ihren Unternehmensdaten und hilft, bislang unentdecktes Potenzial zu entdecken. Dr. Andreas Wierse studierte Mathematik und promovierte in den Ingenieurwissenschaften im Bereich Visualisierung, seit 2011 unterstützt er mittelständische Unternehmen rund um Big und Smart Data Technologie. Dr. Till Riedel lehrt als Informatiker am KIT und koordiniert im Smart Data Solution Center Baden-Württemberg und Smart Data Innovation Lab Forschung und Innovation auf industriellen Datenschätzen.
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Maschinelles Lernen

Author: Ethem Alpaydın

Publisher: Oldenbourg Verlag

ISBN: 9783486581140

Category:

Page: 440

View: 4457

Unter maschinellem Lernen versteht man die kunstliche Generierung von Wissen aus Erfahrung. Das vorliegende Buch diskutiert Methoden aus den Bereichen Statistik, Mustererkennung etc. und versucht, die unterschiedlichen Ansatze zu kombinieren, um moglichst effiziente Losungen zu finden."
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