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Pattern Recognition Principles
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Book Synopsis Pattern Recognition Principles by : Julius T. Tou
Download or read book Pattern Recognition Principles written by Julius T. Tou and published by Addison Wesley Publishing Company. This book was released on 1974 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: The information-handling problem; Basic concepts of pattern recognition; Fundamental problems in pattern recognition system design; Design concepts and methodologies; Decision functions; Pattern classification by distance functions; Pattern classification by likelihood functions; Trainable pattern classifiers - the deterministic approach; Trainable pattern classifiers - the statistical approach; Pattern preprocessing and feature selection; Syntactic pattern recognition.
Book Synopsis Pattern Recognition Principles by : Julius Tsu Lieh Tou
Download or read book Pattern Recognition Principles written by Julius Tsu Lieh Tou and published by . This book was released on 1979 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pattern Recognition by : Jürgen Beyerer
Download or read book Pattern Recognition written by Jürgen Beyerer and published by Walter de Gruyter GmbH & Co KG. This book was released on 2017-12-04 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Pattern Recognition Principles by : J. R. Ullmann
Download or read book Pattern Recognition Principles written by J. R. Ullmann and published by . This book was released on 1973 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Solutions Manual for Pattern Recognition Principles by : Julius T. Tou
Download or read book Solutions Manual for Pattern Recognition Principles written by Julius T. Tou and published by . This book was released on 1975 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pattern Recognition by : Sergios Theodoridis
Download or read book Pattern Recognition written by Sergios Theodoridis and published by Elsevier. This book was released on 2003-05-15 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Pattern Recognition by : Jürgen Beyerer
Download or read book Pattern Recognition written by Jürgen Beyerer and published by Walter de Gruyter GmbH & Co KG. This book was released on 2024-04-01 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Image Processing and Pattern Recognition by : Frank Y. Shih
Download or read book Image Processing and Pattern Recognition written by Frank Y. Shih and published by John Wiley & Sons. This book was released on 2010-07-16 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Pattern Recognition and Neural Networks by : Brian D. Ripley
Download or read book Pattern Recognition and Neural Networks written by Brian D. Ripley and published by Cambridge University Press. This book was released on 2007 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.
Author :A. Ardeshir Goshtasby Publisher :Springer Science & Business Media ISBN 13 :1447124588 Total Pages :454 pages Book Rating :4.4/5 (471 download)
Book Synopsis Image Registration by : A. Ardeshir Goshtasby
Download or read book Image Registration written by A. Ardeshir Goshtasby and published by Springer Science & Business Media. This book was released on 2012-01-11 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a thorough and detailed guide to image registration, outlining the principles and reviewing state-of-the-art tools and methods. The book begins by identifying the components of a general image registration system, and then describes the design of each component using various image analysis tools. The text reviews a vast array of tools and methods, not only describing the principles behind each tool and method, but also measuring and comparing their performances using synthetic and real data. Features: discusses similarity/dissimilarity measures, point detectors, feature extraction/selection and homogeneous/heterogeneous descriptors; examines robust estimators, point pattern matching algorithms, transformation functions, and image resampling and blending; covers principal axes methods, hierarchical methods, optimization-based methods, edge-based methods, model-based methods, and adaptive methods; includes a glossary, an extensive list of references, and an appendix on PCA.
Book Synopsis Probabilistic Graphical Models by : Luis Enrique Sucar
Download or read book Probabilistic Graphical Models written by Luis Enrique Sucar and published by Springer Nature. This book was released on 2020-12-23 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fully updated new edition of a uniquely accessible textbook/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. It features new material on partially observable Markov decision processes, causal graphical models, causal discovery and deep learning, as well as an even greater number of exercises; it also incorporates a software library for several graphical models in Python. The book covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles, and reviews real-world applications for each type of model. These applications are drawn from a broad range of disciplines, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams, and Markov decision processes. Topics and features: Presents a unified framework encompassing all of the main classes of PGMs Explores the fundamental aspects of representation, inference and learning for each technique Examines new material on partially observable Markov decision processes, and graphical models Includes a new chapter introducing deep neural networks and their relation with probabilistic graphical models Covers multidimensional Bayesian classifiers, relational graphical models, and causal models Provides substantial chapter-ending exercises, suggestions for further reading, and ideas for research or programming projects Describes classifiers such as Gaussian Naive Bayes, Circular Chain Classifiers, and Hierarchical Classifiers with Bayesian Networks Outlines the practical application of the different techniques Suggests possible course outlines for instructors This classroom-tested work is suitable as a textbook for an advanced undergraduate or a graduate course in probabilistic graphical models for students of computer science, engineering, and physics. Professionals wishing to apply probabilistic graphical models in their own field, or interested in the basis of these techniques, will also find the book to be an invaluable reference. Dr. Luis Enrique Sucar is a Senior Research Scientist at the National Institute for Astrophysics, Optics and Electronics (INAOE), Puebla, Mexico. He received the National Science Prize en 2016.
Book Synopsis Pattern Recognition and Classification by : Geoff Dougherty
Download or read book Pattern Recognition and Classification written by Geoff Dougherty and published by Springer Science & Business Media. This book was released on 2012-10-28 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Principles of Nonparametric Learning by : Laszlo Györfi
Download or read book Principles of Nonparametric Learning written by Laszlo Györfi and published by Springer. This book was released on 2014-05-04 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides a systematic in-depth analysis of nonparametric learning. It covers the theoretical limits and the asymptotical optimal algorithms and estimates, such as pattern recognition, nonparametric regression estimation, universal prediction, vector quantization, distribution and density estimation, and genetic programming.
Book Synopsis Pattern Recognition by Self-organizing Neural Networks by : Gail A. Carpenter
Download or read book Pattern Recognition by Self-organizing Neural Networks written by Gail A. Carpenter and published by MIT Press. This book was released on 1991 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern Recognition by Self-Organizing Neural Networks presentsthe most recent advances in an area of research that is becoming vitally important in the fields ofcognitive science, neuroscience, artificial intelligence, and neural networks in general. The 19articles take up developments in competitive learning and computational maps, adaptive resonancetheory, and specialized architectures and biological connections. Introductorysurvey articles provide a framework for understanding the many models involved in various approachesto studying neural networks. These are followed in Part 2 by articles that form the foundation formodels of competitive learning and computational mapping, and recent articles by Kohonen, applyingthem to problems in speech recognition, and by Hecht-Nielsen, applying them to problems in designingadaptive lookup tables. Articles in Part 3 focus on adaptive resonance theory (ART) networks,selforganizing pattern recognition systems whose top-down template feedback signals guarantee theirstable learning in response to arbitrary sequences of input patterns. In Part 4, articles describeembedding ART modules into larger architectures and provide experimental evidence fromneurophysiology, event-related potentials, and psychology that support the prediction that ARTmechanisms exist in the brain. Contributors: J.-P. Banquet, G.A. Carpenter, S.Grossberg, R. Hecht-Nielsen, T. Kohonen, B. Kosko, T.W. Ryan, N.A. Schmajuk, W. Singer, D. Stork, C.von der Malsburg, C.L. Winter.
Book Synopsis Psychological Processes in Pattern Recognition by : Stephen K. Reed
Download or read book Psychological Processes in Pattern Recognition written by Stephen K. Reed and published by Academic Press. This book was released on 2013-09-11 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Psychological Processes in Pattern Recognition describes information-processing models of pattern recognition. This book is organized into five parts encompassing 11 chapters that particularly focus on visual pattern recognition and the many issues relevant to a more general theory of pattern recognition. The first three parts cover the representation, temporal effects, and memory codes of pattern recognition. These parts include the features, templates, schemata, and structural descriptions of information processing models. The principles of parallel matching, iconic storage, and the components and networks of memory codes are also considered. The remaining two parts look into the perceptual classification and response selection of pattern recognition. These parts specifically tackle the development of probability, distance, and recognition models. This book is intended primarily for psychologists, graduate students, and researchers who are interested in the problems of pattern recognition and human information processing.
Book Synopsis Pattern Recognition by : Satosi Watanabe
Download or read book Pattern Recognition written by Satosi Watanabe and published by . This book was released on 1985-07-29 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Computational Intelligence for Pattern Recognition by : Witold Pedrycz
Download or read book Computational Intelligence for Pattern Recognition written by Witold Pedrycz and published by Springer. This book was released on 2018-04-30 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and algorithmic issues, as well as implementations and case studies, and identifies the best design practices, assesses business models and practices of pattern recognition in real-world applications in industry, health care, administration, and business. Since the inception of fuzzy sets, fuzzy pattern recognition with its methodology, algorithms, and applications, has offered new insights into the principles and practice of pattern classification. Computational intelligence (CI) establishes a comprehensive framework aimed at fostering the paradigm of pattern recognition. The collection of contributions included in this book offers a representative overview of the advances in the area, with timely, in-depth and comprehensive material on the conceptually appealing and practically sound methodology and practices of CI-based pattern recognition.
