Neural Networks for Pattern Recognition, Bishop, Christopher M.
Автор: Bishop Название: Pattern Recognition and Machine Learning ISBN: 0387310738 ISBN-13(EAN): 9780387310732 Издательство: Springer Рейтинг: Цена: 7947 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: 4162 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: This book constitutes the refereed proceedings of the Second IAPR Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2006, held in Ulm, Germany in August/September 2006. The 26 revised papers presented were carefully reviewed and selected from 49 submissions. The papers are organized in topical sections on unsupervised learning, semi-supervised learning, supervised learning, support vector learning, multiple classifier systems, visual object recognition, and data mining in bioinformatics.
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: Sergios Theodoridis Название: Pattern Recognition, ISBN: 1597492728 ISBN-13(EAN): 9781597492720 Издательство: Elsevier Science Рейтинг: Цена: 8410 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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).
Описание: Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering focuses on fuzzy clustering methods which have proven to be very powerful in pattern recognition and considers the entire process of dynamic pattern recognition. This book sets a general framework for Dynamic Pattern Recognition, describing in detail the monitoring process using fuzzy tools and the adaptation process in which the classifiers have to be adapted, using the observations of the dynamic process. It then focuses on the problem of a changing cluster structure (new clusters, merging of clusters, splitting of clusters and the detection of gradual changes in the cluster structure). Finally, the book integrates these parts into a complete algorithm for dynamic fuzzy classifier design and classification.
Описание: This book presents a statistical treatment of the Multilayer Perceptron (MLP), which is the most widely used of the neural network models, in a language that is familiar to practicing statisticians. Questions arise when statisticians are first confronted with such a model, and this book's aim is to provide thorough answers. The following are a few questions that are considered in this book and are explored: how robust is the model to outliers, could the model be made more robust, which points will have a high leverage, what are good starting values for the fitting algorithm, etc. Discussions include the use of MLP models with spatial data as well as the influence and sensitivity curves of the MLP. The question of why the MLP is a (fairly) robust model is answered and modifications to make it very robust are considered.
Автор: Omid Omidvar Название: Neural Networks and Pattern Recognition, ISBN: 0125264208 ISBN-13(EAN): 9780125264204 Издательство: Elsevier Science Рейтинг: Цена: 7569 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Focuses on the use of neural networks in pattern recognition, an important application area for neural networks technology. This book features neural network architectures on the cutting edge of neural network research, and brings together ideas on dynamical neural networks.
Автор: Gurney, Kevin Название: Introduction to neural networks ISBN: 1857285034 ISBN-13(EAN): 9781857285031 Издательство: Taylor&Francis Рейтинг: Цена: 5955 р. Наличие на складе: Невозможна поставка.
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: 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.
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