Описание: The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the underlying algorithms and techniques. For example, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic techniques. The practical applicability of Bayesian methods has been greatly enhanced by the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation, while new models based on kernels have had a significant impact on both algorithms and applications.A forthcoming companion volume will deal with practical aspects of pattern recognition and machine learning, and will include free software implementations of the key algorithms along with example data sets and demonstration programs.Christopher Bishop is Assistant Director at Microsoft Research Cambridge, and also holds a Chair in Computer Science at the University of Edinburgh. He is a Fellow of Darwin College Cambridge, and was recently elected Fellow of the Royal Academy of Engineering. The author's previous textbook "Neural Networks for Pattern Recognition" has been widely adopted.Coming soon:*For students, worked solutions to a subset of exercises available on a public web site (for exercises marked "www" in the text)*For instructors, worked solutions to remaining exercises from the Springer web site*Lecture slides to accompany each chapter*Data sets available for download
Автор: Brian D. Ripley Название: Pattern Recognition and Neural Networks ISBN: 0521717701 ISBN-13(EAN): 9780521717700 Издательство: Cambridge Academ Рейтинг: Цена: 3746 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Now in paperback: the most reliable account of the statistical framework for pattern recognition and machine learning. With unparalleled coverage and a wealth of case-studies this book gives valuable insight into both the theory and the enormously diverse applications (which can be found in remote sensing, astrophysics, engineering and medicine, for example). So that readers can develop their skills and understanding, many of the real data sets used in the book are available from the author’s website: www.stats.ox.ac.uk/~ripley/PRbook/. For the same reason, many examples are included to illustrate real problems in pattern recognition. Unifying principles are highlighted, and the author gives an overview of the state of the subject, making the book valuable to experienced researchers in statistics, machine learning/artificial intelligence and engineering. The clear writing style means that the book is also a superb introduction for non-specialists.
Описание: 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.
Автор: Gurney, Kevin Название: Introduction to neural networks ISBN: 1857285034 ISBN-13(EAN): 9781857285031 Издательство: Taylor&Francis Рейтинг: Цена: 5015 р. Наличие на складе: Нет в наличии.
Описание: This undergraduate text introduces the fundamentals of neural networks in a gentle but practical fashion with minimal mathematics. It should be of use to students of computer science and engineering, and graduate students in the allied neural
Автор: Franke Название: Pattern Recognition ISBN: 3540444122 ISBN-13(EAN): 9783540444121 Издательство: Springer Рейтинг: Цена: 12154 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 28th Symposium of the German Association for Pattern Recognition, DAGM 2006, held in Berlin,
Germany in September 2006. The 32 revised full papers and 44 revised poster papers presented together with 5 invited papers were carefully reviewed and selected from 171
submissions. The papers are organized in topical sections on image filtering, restoration and segmentation, shape analysis and representation, recognition, categorization and detection,
computer vision and image retrieval, machine learning and statistical data analysis, biomedical data analysis, motion analysis and tracking, pose recognition, stereo and structure from
motion, multi-view image and geometric processing, as well as 3D view registration and surface modelling.
Описание: Pattern recognition presents one of the most significant challenges for scientists and engineers, and many different approaches have been proposed. This book presents an account of probabilistic analysis of these approaches. It includes such topics as distance measures, Vapnik-Chervonenkis theory, epsilon entropy, and parametric classification.
Описание: This volume contains the latest in the series of ICAPR proceedings on the state-of-the-art of different facets of pattern recognition. These conferences have already carved out a unique position among events attended by the pattern recognition community. The contributions tackle open problems in the classic fields of image and video processing, document analysis and multimedia object retrieval as well as more advanced topics in biometrics speech and signal analysis. Many of the papers focus both on theory and application driven basic research pattern recognition.
Описание: The field of biometrics utilizes computer models of the physical and behavioral characteristics of human beings with a view to reliable personal identification. The human characteristics of interest include visual images, speech, and indeed anything which might help to uniquely identify the individual.The other side of the biometrics coin is biometric synthesis - rendering biometric phenomena from their corresponding computer models. For example, we could generate a synthetic face from its corresponding computer model. Such a model could include muscular dynamics to model the full gamut of human emotions conveyed by facial expressions.This book is a collection of carefully selected papers presenting the fundamental theory and practice of various aspects of biometric data processing in the context of pattern recognition. The traditional task of biometric technologies - human identification by analysis of biometric data - is extended to include the new discipline of biometric synthesis.
Описание: "Fuzzy Models and Algorithms for Pattern Recognition and Image Processing" presents a comprehensive introduction of the use of fuzzy models in pattern
ition and selected topics in image processing and computer vision. Unique to this volume in the "Kluwer Handbooks of Fuzzy Sets Series" is the fact that this book was written in its
entirety by its four authors. A single notation, presentation style, and purpose are used throughout.
The result is an extensive unified treatment of many fuzzy models for pattern
recognition. The main topics are clustering and classifier design, with extensive material on feature analysis relational clustering, image processing and computer vision. Also included
are numerous figures, images and numerical examples that illustrate the use of various models involving applications in medicine, character and word recognition, remote sensing, military
image analysis, and industrial engineering.
Описание: 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 3 keynote articles were carefully reviewed and selected from 239 submissions. The pap
rs cover ongoing research and mathematical methods for pattern recognition, image analysis, and applications in such diverse areas as computer vision, robotics and remote sensing,
industry, health, space exploration, data mining, document analysis, natural language processing and speech recognition.
Автор: Bunke Название: Applied Pattern Recognition ISBN: 3540768300 ISBN-13(EAN): 9783540768302 Издательство: Springer Рейтинг: Цена: 15728 р. Наличие на складе: Поставка под заказ.
Описание: A sharp increase in the computing power of modern computers has triggered the development of extremely powerful algorithms. This book intends to cover some of the application domains of pattern recognition while presenting novel techniques that have been developed or customized in those domains.
Автор: Fink, Gernot A. Название: Markov models for pattern recognition ISBN: 3540717668 ISBN-13(EAN): 9783540717669 Издательство: Springer Рейтинг: Цена: 4203 р. Наличие на складе: Поставка под заказ.
Описание: From Theory to Applications.
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