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Advanced Pattern Recognition Techniques
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Book Synopsis Data Complexity in Pattern Recognition by : Mitra Basu
Download or read book Data Complexity in Pattern Recognition written by Mitra Basu and published by Springer Science & Business Media. This book was released on 2006-12-22 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author :North Atlantic Treaty Organization. Research and Technology Organization Publisher : ISBN 13 : Total Pages :172 pages Book Rating :4.:/5 (31 download)
Book Synopsis Advanced Pattern Recognition Techniques by : North Atlantic Treaty Organization. Research and Technology Organization
Download or read book Advanced Pattern Recognition Techniques written by North Atlantic Treaty Organization. Research and Technology Organization and published by . This book was released on 1998 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition is the extraction of consistent information from noisy spatiotemporal data. It can be and is currently being used in systems for battlefield supervision, smart weapons, and anti-counterfeiting of all kinds. A currrent application is the automatic detection of land mines and unexploded ordnance. (UXO). The methods employed can be subdivided in the following manner: (1) statistical methods, (2) neuro - methods, (3) fuzzy - methods, and (4) neuro fuzzy methods. Each of these methods has its special advantages and drawbacks, but all of them require the computation of feature variables from measurement or simulation data, e.g. from microwave backscattering. The Lecture series covers the following topics: (1) Introductory overview on pattern recognition techniques, (1) - (4); (2)Feature extraction for pattern recognition by; (a)Electromagnetic, magnetic, and acoustic singularity identification; (b)Model based scattering signatures; (c) Wavelet techniques; (d) SAR/ISAR imaging; (e)Bistatic microwave imaging; and (f)Electromagnetic inversion techniques; (3) Real-time implementation of pattern recognition methods; and (4)Introduction to software and hardware for pattern recognition.
Book Synopsis Advanced Pattern Recognition Technologies with Applications to Biometrics by : David Zhang
Download or read book Advanced Pattern Recognition Technologies with Applications to Biometrics written by David Zhang and published by IGI Global. This book was released on 2009 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on two kinds of advanced biometric recognition technologies, biometric data discrimination and multi-biometrics"--Provided by publisher.
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 2010-05-03 with total page 564 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.
Author :Giovanni Maria Farinella Publisher :Springer Science & Business Media ISBN 13 :1447155203 Total Pages :437 pages Book Rating :4.4/5 (471 download)
Book Synopsis Advanced Topics in Computer Vision by : Giovanni Maria Farinella
Download or read book Advanced Topics in Computer Vision written by Giovanni Maria Farinella and published by Springer Science & Business Media. This book was released on 2013-09-24 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a broad selection of cutting-edge research, covering both theoretical and practical aspects of reconstruction, registration, and recognition. The text provides an overview of challenging areas and descriptions of novel algorithms. Features: investigates visual features, trajectory features, and stereo matching; reviews the main challenges of semi-supervised object recognition, and a novel method for human action categorization; presents a framework for the visual localization of MAVs, and for the use of moment constraints in convex shape optimization; examines solutions to the co-recognition problem, and distance-based classifiers for large-scale image classification; describes how the four-color theorem can be used for solving MRF problems; introduces a Bayesian generative model for understanding indoor environments, and a boosting approach for generalizing the k-NN rule; discusses the issue of scene-specific object detection, and an approach for making temporal super resolution video.
Book Synopsis Advanced Pattern Recognition Technologies with Applications to Biometrics by : Zhang, David
Download or read book Advanced Pattern Recognition Technologies with Applications to Biometrics written by Zhang, David and published by IGI Global. This book was released on 2009-01-31 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on two kinds of advanced biometric recognition technologies, biometric data discrimination and multi-biometrics"--Provided by publisher.
Book Synopsis Pattern Recognition and Machine Learning by : Christopher M. Bishop
Download or read book Pattern Recognition and Machine Learning written by Christopher M. Bishop and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Book Synopsis Neural Networks for Pattern Recognition by : Christopher M. Bishop
Download or read book Neural Networks for Pattern Recognition written by Christopher M. Bishop and published by Oxford University Press. This book was released on 1995-11-23 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.
Book Synopsis Pattern Recognition Techniques, Technology and Applications by : Danel Jaso
Download or read book Pattern Recognition Techniques, Technology and Applications written by Danel Jaso and published by . This book was released on 2016-04-01 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Pattern Recognition Techniques, Technology and Applications disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition. The book provides comprehensive overview of the developments of techniques and approaches on pattern recognition. Pattern recognition is the science of making inferences from perceptual data, using tools from statistics, probability, computational geometry, machine learning, signal processing, and algorithm design. A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition task. Pattern recognition is the imposition of identity on input data, such as speech, images, or a stream of text, by the recognition and delineation of patterns it contains and their relationships. Stages in pattern recognition may involve measurement of the object to identify distinguishing attributes, extraction of features for the defining attributes, and comparison with known patterns to determine a match or mismatch. Pattern recognition has extensive application in astronomy, medicine, robotics, and remote sensing by satellites."
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 689 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 Techniques Applied to Biomedical Problems by : Martha Refugio Ortiz-Posadas
Download or read book Pattern Recognition Techniques Applied to Biomedical Problems written by Martha Refugio Ortiz-Posadas and published by Springer Nature. This book was released on 2020-02-29 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers pattern recognition techniques applied to various areas of biomedicine, including disease diagnosis and prognosis, and several problems of classification, with a special focus on—but not limited to—pattern recognition modeling of biomedical signals and images. Multidisciplinary by definition, the book’s topic blends computing, mathematics and other technical sciences towards the development of computational tools and methodologies that can be applied to pattern recognition processes. In this work, the efficacy of such methods and techniques for processing medical information is analyzed and compared, and auxiliary criteria for determining the correct diagnosis and treatment strategies are recommended and applied. Researchers in applied mathematics, the computer sciences, engineering and related fields with a focus on medical applications will benefit from this book, as well as professionals with a special interest in state-of-the-art pattern recognition techniques as applied to biomedicine.
Book Synopsis Handbook of Pattern Recognition and Computer Vision by : C. H. Chen
Download or read book Handbook of Pattern Recognition and Computer Vision written by C. H. Chen and published by World Scientific. This book was released on 1999 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.
Book Synopsis Machine Learning and Big Data by : Uma N. Dulhare
Download or read book Machine Learning and Big Data written by Uma N. Dulhare and published by John Wiley & Sons. This book was released on 2020-09-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems. Subjects covered in detail include: Mathematical foundations of machine learning with various examples. An empirical study of supervised learning algorithms like Naïve Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview. Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth. Hands-on machine leaning open source tools viz. Apache Mahout, H2O. Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning. Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on.
Book Synopsis Pattern Recognition Applications and Methods by : Ana Fred
Download or read book Pattern Recognition Applications and Methods written by Ana Fred and published by Springer. This book was released on 2017-02-08 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains revised and extended versions of selected papers from the 5th International Conference on Pattern Recognition, ICPRAM 2016, held in Rome, Italy, in February 2016. The 13 full papers were carefully reviewed and selected from 125 initial submissions and describe up-to-date applications of pattern recognition techniques to real-world problems, interdisciplinary research, experimental and/or theoretical studies yielding new insights that advance pattern recognition methods.
Book Synopsis Pattern Recognition Applications and Methods by : Maria De Marsico
Download or read book Pattern Recognition Applications and Methods written by Maria De Marsico and published by Springer Nature. This book was released on 2020-12-22 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains revised and extended versions of selected papers from the 9th International Conference on Pattern Recognition, ICPRAM 2020, held in Valletta, Malta, in February 2020. The 7 full papers presented were carefully reviewed and selected from 102 initial submissions. The papers describe applications of pattern recognition techniques to real-world problems, interdisciplinary research, experimental and theoretical studies yielding new insights that advance pattern recognition methods are especially encouraged.
Book Synopsis Supervised and Unsupervised Pattern Recognition by : Evangelia Miche Tzanakou
Download or read book Supervised and Unsupervised Pattern Recognition written by Evangelia Miche Tzanakou and published by CRC Press. This book was released on 2017-12-19 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many books on neural networks, some of which cover computational intelligence, but none that incorporate both feature extraction and computational intelligence, as Supervised and Unsupervised Pattern Recognition does. This volume describes the application of a novel, unsupervised pattern recognition scheme to the classification of various types of waveforms and images. This substantial collection of recent research begins with an introduction to Neural Networks, classifiers, and feature extraction methods. It then addresses unsupervised and fuzzy neural networks and their applications to handwritten character recognition and recognition of normal and abnormal visual evoked potentials. The third section deals with advanced neural network architectures-including modular design-and their applications to medicine and three-dimensional NN architecture simulating brain functions. The final section discusses general applications and simulations, such as the establishment of a brain-computer link, speaker identification, and face recognition. In the quickly changing field of computational intelligence, every discovery is significant. Supervised and Unsupervised Pattern Recognition gives you access to many notable findings in one convenient volume.
Book Synopsis Statistical Pattern Recognition by : Andrew R. Webb
Download or read book Statistical Pattern Recognition written by Andrew R. Webb and published by John Wiley & Sons. This book was released on 2003-07-25 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical pattern recognition is a very active area of study andresearch, which has seen many advances in recent years. New andemerging applications - such as data mining, web searching,multimedia data retrieval, face recognition, and cursivehandwriting recognition - require robust and efficient patternrecognition techniques. Statistical decision making and estimationare regarded as fundamental to the study of pattern recognition. Statistical Pattern Recognition, Second Edition has been fullyupdated with new methods, applications and references. It providesa comprehensive introduction to this vibrant area - with materialdrawn from engineering, statistics, computer science and the socialsciences - and covers many application areas, such as databasedesign, artificial neural networks, and decision supportsystems. * Provides a self-contained introduction to statistical patternrecognition. * Each technique described is illustrated by real examples. * Covers Bayesian methods, neural networks, support vectormachines, and unsupervised classification. * Each section concludes with a description of the applicationsthat have been addressed and with further developments of thetheory. * Includes background material on dissimilarity, parameterestimation, data, linear algebra and probability. * Features a variety of exercises, from 'open-book' questions tomore lengthy projects. The book is aimed primarily at senior undergraduate and graduatestudents studying statistical pattern recognition, patternprocessing, neural networks, and data mining, in both statisticsand engineering departments. It is also an excellent source ofreference for technical professionals working in advancedinformation development environments. For further information on the techniques and applicationsdiscussed in this book please visit ahref="http://www.statistical-pattern-recognition.net/"www.statistical-pattern-recognition.net/a
