Pattern Recognition


Author: Sergios Theodoridis,Konstantinos Koutroumbas
Publisher: Elsevier
ISBN: 9780080513614
Category: Computers
Page: 856
View: 5684
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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 in Biology


Author: Marsha S. Corrigan
Publisher: Nova Publishers
ISBN: 9781600217166
Category: Science
Page: 253
View: 9053
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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.

Introduction to Pattern Recognition

Statistical, Structural, Neural, and Fuzzy Logic Approaches
Author: Menahem Friedman,Abraham Kandel
Publisher: World Scientific
ISBN: 9789810233129
Category: Computers
Page: 329
View: 9510
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This book is an introduction to pattern recognition, meant for undergraduate and graduate students in computer science and related fields in science and technology. Most of the topics are accompanied by detailed algorithms and real world applications. In addition to statistical and structural approaches, novel topics such as fuzzy pattern recognition and pattern recognition via neural networks are also reviewed. Each topic is followed by several examples solved in detail. The only prerequisites for using this book are a one-semester course in discrete mathematics and a knowledge of the basic preliminaries of calculus, linear algebra and probability theory.

Pattern Recognition

From Classical to Modern Approaches
Author: Sankar K. Pal,Pal. Amita
Publisher: World Scientific
ISBN: 9789812386533
Category: Computers
Page: 612
View: 8012
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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 Neural Networks


Author: Brian D. Ripley
Publisher: Cambridge University Press
ISBN: 9780521717700
Category: Computers
Page: 403
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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.

Attention and Pattern Recognition


Author: Nick Lund
Publisher: Psychology Press
ISBN: 9780415233095
Category: Psychology
Page: 129
View: 7227
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Introduces the main psychological research on attention and the methods that have been used to study it.

Pattern Recognition


Author: William Gibson
Publisher: Penguin UK
ISBN: 0141904461
Category: Fiction
Page: 368
View: 2306
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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

A Probabilistic Theory of Pattern Recognition


Author: Luc Devroye,László Györfi,Gabor Lugosi
Publisher: Springer Science & Business Media
ISBN: 9780387946184
Category: Mathematics
Page: 638
View: 6642
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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.

Pattern Recognition Methods for Crop Classification from Hyperspectral Remote Sensing Images


Author: Luis Gomez Chova
Publisher: Universal-Publishers
ISBN: 1581122322
Category: Science
Page: 185
View: 7614
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(Complete work in Spanish) Remote sensing aerial spectral imaging was one of the first application areas where spectral imaging was used in order to identify and monitor the natural resources and covers on earth surface. Aerial spectral imaging is being developed with the aim of monitoring natural resources like coastal areas, forestry and extensive crops. The information contained in hyperspectral images allows the reconstruction of the energy curve radiated by the terrestrial surface throughout the electromagnetic spectrum. Hence, the characterization, identification and classification of the observed material from their spectral curve is an interesting possibility. Pattern recognition methods have proven to be effective techniques in this kind of applications. In fact, classification of surface features in satellite imagery is one of the most important applications of remote sensing. It is often difficult and time-consuming to develop classifiers by hand, so many researchers have turned to techniques from the fields of statistics and machine learning to automatically generate classifiers. Nevertheless, the main problem with supervised methods is that the learning process heavily depends on the quality of the training data set and the input space dimensionality. Certainly, these are main issues to be addressed, given the high cost of true sample labeling, the high number of spectral bands, and the high variability of the earth surface and the illumination conditions. In practice, a preprocessing stage (feature selection/extraction) is time-consuming, scenario-dependent and needs a priori knowledge. Thus, more efforts must be done to improve classification methods, in terms of accuracy, robustness, reliability, real-time performance and interpretability. This work is a contribution to the Digital Airborne Imaging Spectrometer Experiment (DAISEX) project, funded by the European Space Agency (ESA) within the framework of its Earth Observation Preparatory Program during 1998, 1999, and 2000. During the DAISEX campaign, hyperspectral images were acquired with the HyMap spectrometer (128-band scanner with a discontinuous spectral range: 0.4 μm - 2.5 μm). In this context, we have carried out an extensive comparison of state-of-the-art methods to develop crop cover classifiers and to obtain a thematic map of the crops on the scene. On one hand, in order to circumvent problems when dealing with a high dimensional input space (induced by the high resolution of the HyMap spectrometer, 128 bands), we have studied a preprocessing stage of feature selection/extraction. This first stage analyses the most critical spectral bands for the present subject. On the other hand, we have developed many methods, both supervised and unsupervised, for crop cover classification, image clustering, interpretation and robustness tests. All these approaches have been included in a general learning scheme where we propose a combined strategy of supervised and unsupervised learning methods that avoids these drawbacks and automates the classification process. In this study, we review the work carried out in that sense and how it could be useful in further applications.

Pattern Recognition

Concepts, Methods, and Applications
Author: J. P. Marques de Sá
Publisher: Springer Science & Business Media
ISBN: 9783540422976
Category: Computers
Page: 318
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CD-ROM contains: Datasets -- Software tools.

Pattern recognition

human and mechanical
Author: Satoshi Watanabe
Publisher: John Wiley & Sons
ISBN: N.A
Category: Computers
Page: 570
View: 4099
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The first major work in the nascent discipline of ``cognitive science.'' It provides a unified presentation of pattern recognition that introduces new mechanical methods as well as a wider humanistic perspective on the science. Showing that practically all the known pattern recognition algorithms can be derived from the principle of minimum entropy, it provides the first complete theory of pattern recognition.

Pattern Recognition

An Algorithmic Approach
Author: M. Narasimha Murty,V. Susheela Devi
Publisher: Springer Science & Business Media
ISBN: 9780857294951
Category: Computers
Page: 263
View: 4714
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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.

Image Processing and Pattern Recognition


Author: Cornelius T. Leondes
Publisher: Elsevier
ISBN: 9780080551449
Category: Computers
Page: 386
View: 693
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Image Processing and Pattern Recognition covers major applications in the field, including optical character recognition, speech classification, medical imaging, paper currency recognition, classification reliability techniques, and sensor technology. The text emphasizes algorithms and architectures for achieving practical and effective systems, and presents many examples. Practitioners, researchers, and students in computer science, electrical engineering, andradiology, as well as those working at financial institutions, will value this unique and authoritative reference to diverse applications methodologies. Coverage includes: Optical character recognition Speech classification Medical imaging Paper currency recognition Classification reliability techniques Sensor technology Algorithms and architectures for achieving practical and effective systems are emphasized, with many examples illustrating the text. Practitioners, researchers, and students in computer science, electrical engineering, and radiology, as wellk as those working at financial institutions, will find this volume a unique and comprehensive reference source for this diverse applications area.

Pattern Recognition

30th DAGM Symposium Munich, Germany, June 10-13, 2008 Proceedings
Author: DAGM (Organization). Symposium
Publisher: Springer Science & Business Media
ISBN: 3540693203
Category: Computers
Page: 538
View: 3271
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This year, 2008, we had a very special Annual Symposium of the Deutsche Arbeitsgemeinschaft fur ¨ Mustererkennung (DAGM) in Munich, and there are several reasons for that. First ofall, this yearwasthe 30th anniversaryof the symposium. Thismeans that the ?rst symposium was organized in 1978 and the location of this event was:Munich!Justtwoyearsbefore,in1976,theDAGMwasfoundedin:Munich! And Munich was also the location of two further DAGM symposia, in 1991 and in 2001. When I attended the conference in 2001, I was in negotiations for my appointmentto the Chair ofHuman–MachineCommunicationatthe Technische Universit¨ atMunc ¨ hen(TUM)andcertainlyIdidnotatallanticipatethatIwould have the pleasure and honor to host this conference just seven years later again in Munich for its 30th anniversary. But special dates are not the only reason why DAGM was somewhat di?- ent this time. This year, DAGM was organized in conjunction with Automatica, the Third International Trade Fair for Automation in Assembly, Robotics, and Vision, one of the world's leading fairs in automation and robotics. This was an ideal platform for the exchange of ideas and people between the symposium and the fair, and the conference thus took place in a somewhat unusual but extra- dinary location, the International Congress Center (ICM), in the direct vicinity of the New Munich Trade Fair Center, the location of the Automatica fair. With free access to Automatica, the registrants of DAGM got the opportunity to make full use of all the synergy e?ects associated with this special arrangement.

Image Processing and Pattern Recognition

Fundamentals and Techniques
Author: Frank Y. Shih
Publisher: John Wiley & Sons
ISBN: 9780470590409
Category: Technology & Engineering
Page: 552
View: 4212
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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.

Introduction to Statistical Pattern Recognition


Author: Keinosuke Fukunaga
Publisher: Elsevier
ISBN: 9780080478654
Category: Computers
Page: 592
View: 716
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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.

Pattern Recognition and Data Mining

Third International Conference on Advances in Pattern Recognition, ICAR 2005, Bath, UK, August 22-25, 2005
Author: Sameer Singh,Maneesha Singh,Chid Apte,Petra Perner
Publisher: Springer Science & Business Media
ISBN: 9783540287575
Category: Computers
Page: 689
View: 7754
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The two volume set LNCS 3686 and LNCS 3687 constitutes the refereed proceedings of the Third International Conference on Advances in Pattern Recognition, ICAPR 2005, held in Bath, UK in August 2005. The papers submitted to ICAPR 2005 were thoroughly reviewed by up to three referees per paper and less than 40% of the submitted papers were accepted. The first volume includes 73 contributions related to Pattern Recognition and Data Mining (which included papers from the tracks of pattern recognition methods, knowledge and learning, and data mining); topics addressed are pattern recognition, data mining, signal processing and OCR/ document analysis. The second volume contains 87 contributions related to Pattern Recognition and Image Analysis (which included papers from the applications track) and deals with security and surveillance, biometrics, image processing and medical imaging. It also contains papers from the Workshop on Pattern Recognition for Crime Prevention.

Neural Networks for Pattern Recognition


Author: Christopher M. Bishop
Publisher: Oxford University Press
ISBN: 0198538642
Category: Computers
Page: 482
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`Readers will emerge with a rigorous statistical grounding in the theory of how to construct and train neural networks in pattern recognition' New Scientist

Advances in Structural and Syntactical Pattern Recognition

6th International Workshop, SSPR' 96, Leipzig, Germany, August, 20 - 23, 1996, Proceedings
Author: Germany) International Workshop on Structural and Syntactic Pattern Recognition (6th : 1996 : Leipzig,Petra Perner,Patrick Wang
Publisher: Springer Science & Business Media
ISBN: 9783540615774
Category: Computers
Page: 392
View: 5468
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This book constitutes the refereed proceedings of the 6th International Workshop on Structural and Syntactical Pattern Recognition, SSPR '96, held in Leipzig, Germany in August 1996. The 36 revised full papers included together with three invited papers were carefully selected from a total of 52 submissions. The papers are organized in topical sections on grammars and languages; morphology and mathematical approaches to pattern recognition; semantic nets, relational models and graph-based methods; 2D and 3D shape recognition; document image analysis and recognition; and handwritten and printed character recognition.

Syntactic and Structural Pattern Recognition

Theory and Applications
Author: Horst Bunke,Alberto Sanfeliu
Publisher: World Scientific
ISBN: 9789971505660
Category: Computers
Page: 554
View: 1033
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This book is currently the only one on this subject containing both introductory material and advanced recent research results. It presents, at one end, fundamental concepts and notations developed in syntactic and structural pattern recognition and at the other, reports on the current state of the art with respect to both methodology and applications. In particular, it includes artificial intelligence related techniques, which are likely to become very important in future pattern recognition.The book consists of individual chapters written by different authors. The chapters are grouped into broader subject areas like “Syntactic Representation and Parsing”, “Structural Representation and Matching”, “Learning”, etc. Each chapter is a self-contained presentation of one particular topic. In order to keep the original flavor of each contribution, no efforts were undertaken to unify the different chapters with respect to notation. Naturally, the self-containedness of the individual chapters results in some redundancy. However, we believe that this handicap is compensated by the fact that each contribution can be read individually without prior study of the preceding chapters. A unification of the spectrum of material covered by the individual chapters is provided by the subject and author index included at the end of the book.