Pattern Recognition

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Pattern Recognition

Pattern Recognition [Pdf/ePub] eBook ISBN-10:
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Publisher: Penguin
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Pattern Recognition by Book Resume:

“Pattern Recognition is William Gibson’s best book since he rewrote all the rules in Neuromancer.”—Neil Gaiman, author of American Gods “One of the first authentic and vital novels of the 21st century.”—The Washington Post Book World The accolades and acclaim are endless for William Gibson's coast-to-coast bestseller. Set in the post-9/11 present, Pattern Recognition is the story of one woman's never-ending search for the now... Cayce Pollard is a new kind of prophet—a world-renowned “coolhunter” who predicts the hottest trends. While in London to evaluate the redesign of a famous corporate logo, she’s offered a different assignment: find the creator of the obscure, enigmatic video clips being uploaded to the internet—footage that is generating massive underground buzz worldwide. Still haunted by the memory of her missing father—a Cold War security guru who disappeared in downtown Manhattan on the morning of September 11, 2001—Cayce is soon traveling through parallel universes of marketing, globalization, and terror, heading always for the still point where the three converge. From London to Tokyo to Moscow, she follows the implications of a secret as disturbing—and compelling—as the twenty-first century promises to be...

Pattern Classification

Pattern Classification [Pdf/ePub] eBook ISBN-10:
Author: Richard O. Duda,Peter E. Hart,David G. Stork
Publisher: John Wiley & Sons
File Size: 336 KB
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Pattern Classification by Richard O. Duda,Peter E. Hart,David G. Stork Book Resume:

The first edition, published in 1973, has become a classicreference in the field. Now with the second edition, readers willfind information on key new topics such as neural networks andstatistical pattern recognition, the theory of machine learning,and the theory of invariances. Also included are worked examples,comparisons between different methods, extensive graphics, expandedexercises and computer project topics. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.

Pattern Recognition

Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Sergios Theodoridis,Konstantinos Koutroumbas
Publisher: Elsevier
File Size: 1826 KB
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Read Count: 1154611

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Pattern Recognition by Sergios Theodoridis,Konstantinos Koutroumbas Book Resume:

Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to "learn" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10 years of teaching experience, the text was developed by the authors through use in their own classrooms. *Approaches pattern recognition from the designer's point of view *New edition highlights latest developments in this growing field, including independent components and support vector machines, not available elsewhere *Supplemented by computer examples selected from applications of interest

Pattern Recognition and Classification

Pattern Recognition and Classification [Pdf/ePub] eBook ISBN-10:
Author: Geoff Dougherty
Publisher: Springer Science & Business Media
File Size: 1071 KB
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Pattern Recognition and Classification by Geoff Dougherty Book Resume:

The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer vision. Fundamental concepts of supervised and unsupervised classification are presented in an informal, rather than axiomatic, treatment so that the reader can quickly acquire the necessary background for applying the concepts to real problems. More advanced topics, such as semi-supervised classification, combining clustering algorithms and relevance feedback are addressed in the later chapters. This book is suitable for undergraduates and graduates studying pattern recognition and machine learning.

Pattern Recognition

Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Konstantinos Koutroumbas,Sergios Theodoridis
Publisher: Academic Press
File Size: 691 KB
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Pattern Recognition by Konstantinos Koutroumbas,Sergios Theodoridis Book Resume:

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

Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: J.P. Marques de Sá
Publisher: Springer Science & Business Media
File Size: 1094 KB
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Pattern Recognition by J.P. Marques de Sá Book Resume:

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

Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: M. Narasimha Murty,V. Susheela Devi
Publisher: Springer Science & Business Media
File Size: 1362 KB
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Pattern Recognition by M. Narasimha Murty,V. Susheela Devi Book Resume:

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

Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Edgar Roman-Rangel,Ángel Fernando Kuri-Morales,José Francisco Martínez-Trinidad,Jesús Ariel Carrasco-Ochoa,José Arturo Olvera-López
Publisher: Springer Nature
File Size: 821 KB
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Read Count: 5577900

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Pattern Recognition by Edgar Roman-Rangel,Ángel Fernando Kuri-Morales,José Francisco Martínez-Trinidad,Jesús Ariel Carrasco-Ochoa,José Arturo Olvera-López Book Resume:

This book constitutes the proceedings of the 13th Mexican Conference on Pattern Recognition, MCPR 2021, which was planned to be held in Mexico City, Mexico, in June 2021. The conference was instead held virtually. The 35 papers presented in this volume were carefully reviewed and selected from 75 submissions. They are organized in the following topical sections: artificial intelligence techniques and recognition; pattern recognition techniques; neural networks and deep learning; computer vision; image processing and analysis; and medical applications of pattern recognition.

Introduction to Pattern Recognition

Introduction to Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Sergios Theodoridis,Aggelos Pikrakis,Konstantinos Koutroumbas,Dionisis Cavouras
Publisher: Academic Press
File Size: 1112 KB
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Introduction to Pattern Recognition by Sergios Theodoridis,Aggelos Pikrakis,Konstantinos Koutroumbas,Dionisis Cavouras Book Resume:

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)

Trade What You See

Trade What You See [Pdf/ePub] eBook ISBN-10:
Author: Larry Pesavento,Leslie Jouflas
Publisher: John Wiley & Sons
File Size: 1082 KB
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Trade What You See by Larry Pesavento,Leslie Jouflas Book Resume:

Trading the financial markets is extremely difficult, but with the right approach, traders can achieve success. Nobody knows this better than authors Larry Pesavento and Leslie Jouflas, both traders and educators of traders, who have consistently used pattern recognition to capture profits from the markets. In Trade What You See, Pesavento and Jouflas show traders how to identify patterns as they are developing and exactly where to place entry and exit orders. While some patterns derive from the techniques of Wall Street’s earliest traders and other patterns reflect Pesavento’s emphasis on the geometry of market movements and Fibonacci numbers.. Filled with hard-won knowledge gained through years of market experience, Trade What You Seeoutlines both a practical and sophisticated approach to trading that will be of interest to both novice and seasoned traders alike. Larry Pesavento is a forty-year veteran trader. He operates a Web site,

Attention and Pattern Recognition

Attention and Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Nick Lund
Publisher: Routledge
File Size: 1385 KB
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Attention and Pattern Recognition by Nick Lund Book Resume:

Whilst attention is a term commonly used in everyday life, for many years psychologists have struggled in their attempts to explain what it actually means. Attention and Pattern Recognition introduces the main psychological research on attention and the methods that have been used to study it. It also examines the subdivisions of focused and divided attention and explores how people recognise patterns and faces. The Routledge Modular Psychology series is a completely new approach to introductory level psychology, tailor made to the new modular style of teaching. Each short book covers a topic in more detail than any large textbook can, allowing teacher and student to select material exactly to suit any particular course or project. The books have been written especially for those students new to higher level study, whether at school home, college or university. They include specially designed features to help with technique, such as model essay at an average level with an examiners comments to show how extra marks can be gained. The authors are all examiners and teachers at introductory level.

Error Estimation for Pattern Recognition

Error Estimation for Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Ulisses M. Braga Neto,Edward R. Dougherty
Publisher: John Wiley & Sons
File Size: 1803 KB
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Error Estimation for Pattern Recognition by Ulisses M. Braga Neto,Edward R. Dougherty Book Resume:

This book is the first of its kind to discuss error estimation with a model-based approach. From the basics of classifiers and error estimators to distributional and Bayesian theory, it covers important topics and essential issues pertaining to the scientific validity of pattern classification. Error Estimation for Pattern Recognition focuses on error estimation, which is a broad and poorly understood topic that reaches all research areas using pattern classification. It includes model-based approaches and discussions of newer error estimators such as bolstered and Bayesian estimators. This book was motivated by the application of pattern recognition to high-throughput data with limited replicates, which is a basic problem now appearing in many areas. The first two chapters cover basic issues in classification error estimation, such as definitions, test-set error estimation, and training-set error estimation. The remaining chapters in this book cover results on the performance and representation of training-set error estimators for various pattern classifiers. Additional features of the book include: • The latest results on the accuracy of error estimation • Performance analysis of re-substitution, cross-validation, and bootstrap error estimators using analytical and simulation approaches • Highly interactive computer-based exercises and end-of-chapter problems This is the first book exclusively about error estimation for pattern recognition. Ulisses M. Braga Neto is an Associate Professor in the Department of Electrical and Computer Engineering at Texas A&M University, USA. He received his PhD in Electrical and Computer Engineering from The Johns Hopkins University. Dr. Braga Neto received an NSF CAREER Award for his work on error estimation for pattern recognition with applications in genomic signal processing. He is an IEEE Senior Member. Edward R. Dougherty is a Distinguished Professor, Robert F. Kennedy ’26 Chair, and Scientific Director at the Center for Bioinformatics and Genomic Systems Engineering at Texas A&M University, USA. He is a fellow of both the IEEE and SPIE, and he has received the SPIE Presidents Award. Dr. Dougherty has authored several books including Epistemology of the Cell: A Systems Perspective on Biological Knowledge and Random Processes for Image and Signal Processing (Wiley-IEEE Press).

Introduction to Pattern Recognition

Introduction to Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Menahem Friedman,Abraham Kandel
Publisher: World Scientific Publishing Company
File Size: 532 KB
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Read Count: 507362

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Introduction to Pattern Recognition by Menahem Friedman,Abraham Kandel Book Resume:

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.

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

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications [Pdf/ePub] eBook ISBN-10:
Author: Ingela Nyström,Yanio Hernández Heredia,Vladimir Milián Núñez
Publisher: Springer Nature
File Size: 1742 KB
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Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications by Ingela Nyström,Yanio Hernández Heredia,Vladimir Milián Núñez Book Resume:

This book constitutes the refereed conference proceedings of the 24rd Iberoamerican Congress on Pattern Recognition, CIARP 2019, held in Havana, Cuba, in October 2019. The 70 papers presented were carefully reviewed and selected from 128 submissions. The papers are organized in topical sections named: Data Mining: Natural Language Processing and Text Mining; Image Analysis and Retrieval; Machine Learning and Neural Networks; Mathematical Theory of Pattern Recognition; Pattern Recognition and Applications; Signals Analysis and Processing; Speech Recognition; Video Analysis.

Pattern Recognition

Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Jürgen Beyerer,Matthias Richter,Matthias Nagel
Publisher: Walter de Gruyter GmbH & Co KG
File Size: 1560 KB
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Pattern Recognition by Jürgen Beyerer,Matthias Richter,Matthias Nagel Book Resume:

The book offers a thorough introduction to Pattern Recognition aimed at master and advanced bachelor students of engineering and the natural sciences. Besides classification - the heart of Pattern Recognition - special emphasis is put on features, their typology, their properties and their systematic construction. Additionally, general principles that govern Pattern Recognition are illustrated and explained in a comprehensible way. Rather than presenting a complete overview over the rapidly evolving field, the book is to clarifies the concepts so that the reader can easily understand the underlying ideas and the rationale behind the methods. For this purpose, the mathematical treatment of Pattern Recognition is pushed so far that the mechanisms of action become clear and visible, but not farther. Therefore, not all derivations are driven into the last mathematical detail, as a mathematician would expect it. Ideas of proofs are presented instead of complete proofs. From the authors’ point of view, this concept allows to teach the essential ideas of Pattern Recognition with sufficient depth within a relatively lean book. Mathematical methods explained thoroughly Extremely practical approach with many examples Based on over ten years lecture at Karlsruhe Institute of Technology For students but also for practitioners

Pattern Recognition

Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Brett Anderson
Publisher: Scientific e-Resources
File Size: 489 KB
File Format: Pdf
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Pattern Recognition by Brett Anderson Book Resume:

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.

Pattern Recognition. ICPR International Workshops and Challenges

Pattern Recognition. ICPR International Workshops and Challenges [Pdf/ePub] eBook ISBN-10:
Author: Alberto Del Bimbo,Rita Cucchiara,Stan Sclaroff,Giovanni Maria Farinella,Tao Mei,Marco Bertini,Hugo Jair Escalante,Roberto Vezzani
Publisher: Springer Nature
File Size: 934 KB
File Format: Pdf
Read Count: 4116736

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Pattern Recognition. ICPR International Workshops and Challenges by Alberto Del Bimbo,Rita Cucchiara,Stan Sclaroff,Giovanni Maria Farinella,Tao Mei,Marco Bertini,Hugo Jair Escalante,Roberto Vezzani Book Resume:

This 8-volumes set constitutes the refereed of the 25th International Conference on Pattern Recognition Workshops, ICPR 2020, held virtually in Milan, Italy and rescheduled to January 10 - 11, 2021 due to Covid-19 pandemic. The 416 full papers presented in these 8 volumes were carefully reviewed and selected from about 700 submissions. The 46 workshops cover a wide range of areas including machine learning, pattern analysis, healthcare, human behavior, environment, surveillance, forensics and biometrics, robotics and egovision, cultural heritage and document analysis, retrieval, and women at ICPR2020.

Fundamentals of Pattern Recognition and Machine Learning

Fundamentals of Pattern Recognition and Machine Learning [Pdf/ePub] eBook ISBN-10:
Author: Ulisses Braga-Neto
Publisher: Springer Nature
File Size: 1442 KB
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Fundamentals of Pattern Recognition and Machine Learning by Ulisses Braga-Neto Book Resume:

Fundamentals of Pattern Recognition and Machine Learning is designed for a one or two-semester introductory course in Pattern Recognition or Machine Learning at the graduate or advanced undergraduate level. The book combines theory and practice and is suitable to the classroom and self-study. It has grown out of lecture notes and assignments that the author has developed while teaching classes on this topic for the past 13 years at Texas A&M University. The book is intended to be concise but thorough. It does not attempt an encyclopedic approach, but covers in significant detail the tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as Gaussian process regression and convolutional neural networks. In addition, the selection of topics has a few features that are unique among comparable texts: it contains an extensive chapter on classifier error estimation, as well as sections on Bayesian classification, Bayesian error estimation, separate sampling, and rank-based classification. The book is mathematically rigorous and covers the classical theorems in the area. Nevertheless, an effort is made in the book to strike a balance between theory and practice. In particular, examples with datasets from applications in bioinformatics and materials informatics are used throughout to illustrate the theory. These datasets are available from the book website to be used in end-of-chapter coding assignments based on python and scikit-learn. All plots in the text were generated using python scripts, which are also available on the book website.

Progress in Pattern Recognition, Image Analysis and Applications

Progress in Pattern Recognition, Image Analysis and Applications [Pdf/ePub] eBook ISBN-10:
Author: José Francisco Martínez-Trinidad,Jesús Ariel Carrasco Ochoa,Josef Kittler
Publisher: Springer
File Size: 989 KB
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Read Count: 4090671

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Progress in Pattern Recognition, Image Analysis and Applications by José Francisco Martínez-Trinidad,Jesús Ariel Carrasco Ochoa,Josef Kittler Book Resume:

This book constitutes the refereed proceedings of the 11th Iberoamerican Congress on Pattern Recognition, CIARP 2006, held in Cancun, Mexico in November 2006. The 99 revised full papers presented together with three keynote articles were carefully reviewed and selected from 239 submissions. The papers cover ongoing research and mathematical methods.

Progress in Pattern Recognition, Speech and Image Analysis

Progress in Pattern Recognition, Speech and Image Analysis [Pdf/ePub] eBook ISBN-10:
Author: Alberto Sanfeliu,José Ruiz-Shulcloper
Publisher: Springer
File Size: 895 KB
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Read Count: 5055121

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Progress in Pattern Recognition, Speech and Image Analysis by Alberto Sanfeliu,José Ruiz-Shulcloper Book Resume:

CIARP 2003 (8th Iberoamerican Congress on Pattern Recognition) was the eighth event in a series of pioneering congresses on pattern recognition in the Latin American c- munity of countries. This year, however, the forum was extended to include worldwide participation. The event has been held in the past in Mexico, Cuba, Brazil and Por- gal; it took place this year in Havana (Cuba). The aim of the congress was to promote and disseminate ongoing research into mathematical methods for pattern recognition, computer vision, image analysis, and speech recognition, as well as the application of these techniques in such diverse areas as robotics, industry, health, entertainment, space exploration, telecommunications, data mining, document analysis, and natural language processing and recognition to name a few. Moreover it was a forum for scienti?c re- arch, experience exchange, the sharing of new knowledge, and establishing contacts to improve cooperation between research groups in pattern recognition, computer vision and related areas. The congress was organized by the Institute of Cybernetics, Mathematics and P- sics of Cuba (ICIMAF) and the Center for Computing Research (CIC) of the National Polytechnic Institute of Mexico, and was sponsored by the University of La Salle, - xico, the University of Oriente, Cuba, the Polytechnic Institute “Jose ́ A.

Data Complexity in Pattern Recognition

Data Complexity in Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Mitra Basu,Tin Kam Ho
Publisher: Springer Science & Business Media
File Size: 414 KB
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Read Count: 3035222

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Data Complexity in Pattern Recognition by Mitra Basu,Tin Kam Ho Book Resume:

Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of current classification techniques, and the algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance.

Pattern Recognition with Fuzzy Objective Function Algorithms

Pattern Recognition with Fuzzy Objective Function Algorithms [Pdf/ePub] eBook ISBN-10:
Author: James C. Bezdek
Publisher: Springer Science & Business Media
File Size: 1033 KB
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Pattern Recognition with Fuzzy Objective Function Algorithms by James C. Bezdek Book Resume:

The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question of whether or not a group of objects form a cluster. A pioneering application of the theory of fuzzy sets to cluster analysis was made in 1969 by Ruspini. It was not until 1973, however, when the appearance of the work by Dunn and Bezdek on the Fuzzy ISODATA (or fuzzy c-means) algorithms became a landmark in the theory of cluster analysis, that the relevance of the theory of fuzzy sets to cluster analysis and pattern recognition became clearly established. Since then, the theory of fuzzy clustering has developed rapidly and fruitfully, with the author of the present monograph contributing a major share of what we know today. In their seminal work, Bezdek and Dunn have introduced the basic idea of determining the fuzzy clusters by minimizing an appropriately defined functional, and have derived iterative algorithms for computing the membership functions for the clusters in question. The important issue of convergence of such algorithms has become much better understood as a result of recent work which is described in the monograph.

A Probabilistic Theory of Pattern Recognition

A Probabilistic Theory of Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Luc Devroye,Laszlo Györfi,Gabor Lugosi
Publisher: Springer Science & Business Media
File Size: 943 KB
File Format: Pdf
Read Count: 3680290

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A Probabilistic Theory of Pattern Recognition by Luc Devroye,Laszlo Györfi,Gabor Lugosi Book Resume:

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.

Applied Pattern Recognition

Applied Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Horst Bunke,Abraham Kandel,Mark Last
Publisher: Springer
File Size: 1118 KB
File Format: Pdf
Read Count: 6807216

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Applied Pattern Recognition by Horst Bunke,Abraham Kandel,Mark Last Book Resume:

A sharp increase in the computing power of modern computers has triggered the development of powerful algorithms that can analyze complex patterns in large amounts of data within a short time period. Consequently, it has become possible to apply pattern recognition techniques to new tasks. The main goal of this book is to cover some of the latest application domains of pattern recognition while presenting novel techniques that have been developed or customized in those domains.

Pattern Recognition

Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Jesús Ariel Carrasco-Ochoa,José Francisco Martínez-Trinidad,Juan Humberto Sossa-Azuela,José Arturo Olvera López,Fazel Famili
Publisher: Springer
File Size: 991 KB
File Format: Pdf
Read Count: 7637281

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Pattern Recognition by Jesús Ariel Carrasco-Ochoa,José Francisco Martínez-Trinidad,Juan Humberto Sossa-Azuela,José Arturo Olvera López,Fazel Famili Book Resume:

This book constitutes the refereed proceedings of the 7th Mexican Conference on Pattern Recognition, MCPR 2015, held in Mexico City Mexico, in June 2015. The 30 revised full papers presented were carefully reviewed and selected from 63 submissions. The papers are organized in topical sections on pattern recognition and artificial intelligence; image processing and analysis; robotics and computer vision; natural language processing and recognition; and applications of pattern recognition.

Markov Models for Pattern Recognition

Markov Models for Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Gernot A. Fink
Publisher: Springer Science & Business Media
File Size: 300 KB
File Format: Pdf
Read Count: 1495316

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Markov Models for Pattern Recognition by Gernot A. Fink Book Resume:

This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n-best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models.

Pattern Recognition and Classification in Time Series Data

Pattern Recognition and Classification in Time Series Data [Pdf/ePub] eBook ISBN-10:
Author: Volna, Eva,Kotyrba, Martin,Janosek, Michal
Publisher: IGI Global
File Size: 1216 KB
File Format: Pdf
Read Count: 3005514

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Pattern Recognition and Classification in Time Series Data by Volna, Eva,Kotyrba, Martin,Janosek, Michal Book Resume:

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.

Introduction to Pattern Recognition and Machine Learning

Introduction to Pattern Recognition and Machine Learning [Pdf/ePub] eBook ISBN-10:
Author: M Narasimha Murty,V Susheela Devi
Publisher: World Scientific
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Introduction to Pattern Recognition and Machine Learning by M Narasimha Murty,V Susheela Devi Book Resume:

This book adopts a detailed and methodological algorithmic approach to explain the concepts of pattern recognition. While the text provides a systematic account of its major topics such as pattern representation and nearest neighbour based classifiers, current topics — neural networks, support vector machines and decision trees — attributed to the recent vast progress in this field are also dealt with. Introduction to Pattern Recognition and Machine Learning will equip readers, especially senior computer science undergraduates, with a deeper understanding of the subject matter. Contents:IntroductionTypes of DataFeature Extraction and Feature SelectionBayesian LearningClassificationClassification Using Soft Computing TechniquesData ClusteringSoft ClusteringApplication — Social and Information Networks Readership: Academics and working professionals in computer science. Key Features:The algorithmic approach taken and the practical issues dealt with will aid the reader in writing programs and implementing methodsCovers recent and advanced topics by providing working exercises, examples and illustrations in each chapterProvides the reader with a deeper understanding of the subject matterKeywords:Clustering;Classification;Supervised Learning;Soft Computing

Progress in Pattern Recognition, Image Analysis and Applications

Progress in Pattern Recognition, Image Analysis and Applications [Pdf/ePub] eBook ISBN-10:
Author: José Ruiz-Shulcloper,Walter Kropatsch
Publisher: Springer
File Size: 812 KB
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Progress in Pattern Recognition, Image Analysis and Applications by José Ruiz-Shulcloper,Walter Kropatsch Book Resume:

This book constitutes the refereed proceedings of the 13th Iberoamerican Congress on Pattern Recognition, CIARP 2008, held in Havana, Cuba, in September 2008. The 93 revised full papers presented together with 3 keynote articles were carefully reviewed and selected from 182 submissions. The papers are organized in topical sections on signal analysis for characterization and filtering, analysis of shape and texture, analysis of speech and language, data mining, clustering of images and documents, statistical pattern recognition, classification and description of objects, classification and edition, geometric image analysis, neural networks, computer vision, image coding, associative memories and neural networks, interpolation and video tracking, images analysis, music and speech analysis, as well as classifier combination and document filtering.

Advances in Pattern Recognition - ICAPR 2001

Advances in Pattern Recognition - ICAPR 2001 [Pdf/ePub] eBook ISBN-10:
Author: Sameer Singh,Nabeel Murshed,Walter Kropatsch
Publisher: Springer
File Size: 541 KB
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Read Count: 2017879

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Advances in Pattern Recognition - ICAPR 2001 by Sameer Singh,Nabeel Murshed,Walter Kropatsch Book Resume:

The paper is organized as follows: In section 2, we describe the no- orientation-discontinuity interfering model based on a Gaussian stochastic model in analyzing the properties of the interfering strokes. In section 3, we describe the improved canny edge detector with an ed- orientation constraint to detect the edges and recover the weak ones of the foreground words and characters; In section 4, we illustrate, discuss and evaluate the experimental results of the proposed method, demonstrating that our algorithm significantly improves the segmentation quality; Section 5 concludes this paper. 2. The norm-orientation-discontinuity interfering stroke model Figure 2 shows three typical samples of original image segments from the original documents and their magnitude of the detected edges respectively. The magnitude of the gradient is converted into the gray level value. The darker the edge is, the larger is the gradient magnitude. It is obvious that the topmost strong edges correspond to foreground edges. It should be noted that, while usually, the foreground writing appears darker than the background image, as shown in sample image Figure 2(a), there are cases where the foreground and background have similar intensities as shown in Figure 2(b), or worst still, the background is more prominent than the foreground as in Figure 2(c). So using only the intensity value is not enough to differentiate the foreground from the background. (a) (b) (c) (d) (e) (f)

Pattern Recognition Applications in Engineering

Pattern Recognition Applications in Engineering [Pdf/ePub] eBook ISBN-10:
Author: Burgos, Diego Alexander Tibaduiza,Vejar, Maribel Anaya,Pozo, Francesc
Publisher: IGI Global
File Size: 1220 KB
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Pattern Recognition Applications in Engineering by Burgos, Diego Alexander Tibaduiza,Vejar, Maribel Anaya,Pozo, Francesc Book Resume:

The implementation of data and information analysis has become a trending solution within multiple professions. New tools and approaches are continually being developed within data analysis to further solve the challenges that come with professional strategy. Pattern recognition is an innovative method that provides comparison techniques and defines new characteristics within the information acquisition process. Despite its recent trend, a considerable amount of research regarding pattern recognition and its various strategies is lacking. Pattern Recognition Applications in Engineering is an essential reference source that discusses various strategies of pattern recognition algorithms within industrial and research applications and provides examples of results in different professional areas including electronics, computation, and health monitoring. Featuring research on topics such as condition monitoring, data normalization, and bio-inspired developments, this book is ideally designed for analysts; researchers; civil, mechanical, and electronic engineers; computing scientists; chemists; academicians; and students.

UNSUPERVISED LEARNING TECHNIQUES: PATTERN RECOGNITION. EXAMPLES WITH MATLAB

UNSUPERVISED LEARNING TECHNIQUES: PATTERN RECOGNITION. EXAMPLES WITH MATLAB [Pdf/ePub] eBook ISBN-10:
Author: César Pérez López
Publisher: Lulu Press, Inc
File Size: 1948 KB
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Read Count: 4104084

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UNSUPERVISED LEARNING TECHNIQUES: PATTERN RECOGNITION. EXAMPLES WITH MATLAB by César Pérez López Book Resume:

Machine learning uses two types of techniques: supervised learning, which trains a model on known input and output data so that it can predict future outputs, and unsupervised learning, which finds hidden patterns or intrinsic structures in input data. Unsupervised learning finds hidden patterns or intrinsic structures in data. It is used to draw inferences from datasets consisting of input data without labeled responses. Clustering is the most common unsupervised learning technique. It is used for exploratory data analysis to find hidden patterns or groupings in data. Applications for clustering include gene sequence analysis, market research, and object recognition. This book develops pattern recognition techniques.

Pattern Recognition and Artificial Intelligence

Pattern Recognition and Artificial Intelligence [Pdf/ePub] eBook ISBN-10:
Author: C.H. Chen
Publisher: Elsevier
File Size: 613 KB
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Read Count: 3136839

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Pattern Recognition and Artificial Intelligence by C.H. Chen Book Resume:

Pattern Recognition and Artificial Intelligence contains the proceedings of the Joint Workshop on Pattern Recognition and Artificial Intelligence held in Hyannis, Massachusetts, on June 1-3, 1976. The papers explore developments in pattern recognition and artificial intelligence and cover topics ranging from scene analysis and data structure to syntactic methods, biomedicine, speech recognition, game-playing programs, and computer graphics. Grammar inference methods, image segmentation and interpretation, and relational databases are also discussed. This book is comprised of 29 chapters and begins with a description of a data structure that can learn simple programs from training samples. The reader is then introduced to the syntactic parts of pattern recognition systems; methods for multidimensional grammatical inference; a scene analysis system capable of finding structure in outdoor scenes; and a language called DEDUCE for relational databases. A sculptor's studio-like environment, in which the ""sculptor"" can create complex three-dimensional objects in the computer similar to molding a piece of clay in the machine, is also described. The remaining chapters focus on statistical and structural feature extraction; use of maximum likelihood functions for recognition of highly variable line drawings; region extraction using boundary following; and interactive screening of reconnaissance imagery. This monograph will be of interest to engineers, graduate students, and researchers in the fields of pattern recognition and artificial intelligence.

Pattern Recognition and Machine Intelligence

Pattern Recognition and Machine Intelligence [Pdf/ePub] eBook ISBN-10:
Author: Bhabesh Deka,Pradipta Maji,Sushmita Mitra,Dhruba Kumar Bhattacharyya,Prabin Kumar Bora,Sankar Kumar Pal
Publisher: Springer Nature
File Size: 1232 KB
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Read Count: 3372106

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Pattern Recognition and Machine Intelligence by Bhabesh Deka,Pradipta Maji,Sushmita Mitra,Dhruba Kumar Bhattacharyya,Prabin Kumar Bora,Sankar Kumar Pal Book Resume:

The two-volume set of LNCS 11941 and 11942 constitutes the refereed proceedings of the 8th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2019, held in Tezpur, India, in December 2019. The 131 revised full papers presented were carefully reviewed and selected from 341 submissions. They are organized in topical sections named: Pattern Recognition; Machine Learning; Deep Learning; Soft and Evolutionary Computing; Image Processing; Medical Image Processing; Bioinformatics and Biomedical Signal Processing; Information Retrieval; Remote Sensing; Signal and Video Processing; and Smart and Intelligent Sensors.

Pattern Recognition and Machine Intelligence

Pattern Recognition and Machine Intelligence [Pdf/ePub] eBook ISBN-10:
Author: Ashish Ghosh,Rajat K. De,Sankar K Pal
Publisher: Springer
File Size: 990 KB
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Pattern Recognition and Machine Intelligence by Ashish Ghosh,Rajat K. De,Sankar K Pal Book Resume:

This book constitutes the refereed proceedings of the Second International Conference on Pattern Recognition and Machine Intelligence, PReMI 2007, held in Kolkata, India in December 2007. The papers are organized in topical sections on pattern recognition, image analysis, soft computing and applications, data mining and knowledge discovery, bioinformatics, signal and speech processing, document analysis and text mining, biometrics, and video analysis.

Rough-Fuzzy Pattern Recognition

Rough-Fuzzy Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Pradipta Maji,Sankar K. Pal
Publisher: John Wiley & Sons
File Size: 1536 KB
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Read Count: 2694590

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Rough-Fuzzy Pattern Recognition by Pradipta Maji,Sankar K. Pal Book Resume:

Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems development, making it easier to master such tasks as classification, clustering, and feature selection. Rough-Fuzzy Pattern Recognition examines the important underlying theory as well as algorithms and applications, helping readers see the connections between theory and practice. The first chapter provides an introduction to pattern recognition and data mining, including the key challenges of working with high-dimensional, real-life data sets. Next, the authors explore such topics and issues as: Soft computing in pattern recognition and data mining A Mathematical framework for generalized rough sets, incorporating the concept of fuzziness in defining the granules as well as the set Selection of non-redundant and relevant features of real-valued data sets Selection of the minimum set of basis strings with maximum information for amino acid sequence analysis Segmentation of brain MR images for visualization of human tissues Numerous examples and case studies help readers better understand how pattern recognition models are developed and used in practice. This text—covering the latest findings as well as directions for future research—is recommended for both students and practitioners working in systems design, pattern recognition, image analysis, data mining, bioinformatics, soft computing, and computational intelligence.

Statistical Pattern Recognition

Statistical Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Andrew R. Webb,Keith D. Copsey
Publisher: John Wiley & Sons
File Size: 850 KB
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Read Count: 5670089

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Statistical Pattern Recognition by Andrew R. Webb,Keith D. Copsey Book Resume:

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields, including the areas of engineering, statistics, computer science and the social sciences. The book has been updated to cover new methods and applications, and includes a wide range of techniques such as Bayesian methods, neural networks, support vector machines, feature selection and feature reduction techniques.Technical descriptions and motivations are provided, and the techniques are illustrated using real examples. Statistical Pattern Recognition, 3rd Edition: Provides a self-contained introduction to statistical pattern recognition. Includes new material presenting the analysis of complex networks. Introduces readers to methods for Bayesian density estimation. Presents descriptions of new applications in biometrics, security, finance and condition monitoring. Provides descriptions and guidance for implementing techniques, which will be invaluable to software engineers and developers seeking to develop real applications Describes mathematically the range of statistical pattern recognition techniques. Presents a variety of exercises including more extensive computer projects. The in-depth technical descriptions make the book suitable for senior undergraduate and graduate students in statistics, computer science and engineering. Statistical Pattern Recognition is also an excellent reference source for technical professionals. Chapters have been arranged to facilitate implementation of the techniques by software engineers and developers in non-statistical engineering fields. www.wiley.com/go/statistical_pattern_recognition

Pattern Recognition and Image Analysis

Pattern Recognition and Image Analysis [Pdf/ePub] eBook ISBN-10:
Author: Francisco J. Perales López,Aurélio J.C. Campilho,Nicolás Pérez de la Blanca Capilla,Alberto Sanfeliu i Cortés
Publisher: Springer
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Read Count: 8704025

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Pattern Recognition and Image Analysis by Francisco J. Perales López,Aurélio J.C. Campilho,Nicolás Pérez de la Blanca Capilla,Alberto Sanfeliu i Cortés Book Resume:

The refereed proceedings of the First Iberial Conference on Pattern Recognition and Image Analysis, IbPria 2003, held in Puerto de Andratx, Mallorca, Spain in June 2003. The 130 revised papers presented were carefully reviewed and selected from 185 full papers submitted. All current aspects of ongoing research in computer vision, image processing, pattern recognition, and speech recognition are addressed.

Pattern Recognition Applications and Methods

Pattern Recognition Applications and Methods [Pdf/ePub] eBook ISBN-10:
Author: Maria De Marsico,Gabriella Sanniti di Baja,Ana Fred
Publisher: Springer Nature
File Size: 1860 KB
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Read Count: 6853531

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Pattern Recognition Applications and Methods by Maria De Marsico,Gabriella Sanniti di Baja,Ana Fred Book Resume:

This book contains revised and extended versions of selected papers from the 8th International Conference on Pattern Recognition, ICPRAM 2019, held in Prague, Czech Republic, in February 2019. The 25 full papers presented together 52 short papers and 32 poster sessions were carefully reviewed and selected from 138 initial submissions. Contributions describing applications of Pattern Recognition techniques to real-world problems, interdisciplinary research, experimental and/or theoretical studies yielding new insights that advance Pattern Recognition methods are especially encouraged.

Computational Intelligence in Pattern Recognition

Computational Intelligence in Pattern Recognition [Pdf/ePub] eBook ISBN-10:
Author: Asit Kumar Das,Janmenjoy Nayak,Bighnaraj Naik,Soumi Dutta,Danilo Pelusi
Publisher: Springer Nature
File Size: 1700 KB
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Read Count: 3601733

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Computational Intelligence in Pattern Recognition by Asit Kumar Das,Janmenjoy Nayak,Bighnaraj Naik,Soumi Dutta,Danilo Pelusi Book Resume:

This book features high-quality research papers presented at the 3rd International Conference on Computational Intelligence in Pattern Recognition (CIPR 2021), held at the Institute of Engineering and Management, Kolkata, West Bengal, India, on 24 – 25 April 2021. It includes practical development experiences in various areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.