Markov Models for Pattern Recognition, Gernot A. Fink

Автор: Brian D. Ripley
Название: Pattern Recognition and Neural Networks
ISBN: 0521717701 ISBN-13(EAN): 9780521717700
Издательство: Cambridge Academ
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Описание: This 1996 book is a reliable account of the statistical framework for pattern recognition and machine learning. Valuable advice is included on both theory and applications, while case studies based on real data sets help readers develop their understanding. All data sets are available from www.stats.ox.ac.uk/~ripley/PRbook/

Автор: Sergios Theodoridis
Название: Introduction to Pattern Recognition: A Matlab Approach,
ISBN: 0123744865 ISBN-13(EAN): 9780123744869
Издательство: Elsevier Science
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Описание: An accompanying manual to "Theodoridis/Koutroumbas, Pattern Recognition", that 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.

Автор: Fink, Gernot A.
Название: Markov models for pattern recognition
ISBN: 1447163079 ISBN-13(EAN): 9781447163077
Издательство: Springer
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Цена: 10480.00 р.
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Описание: This book places the formalism of Markov chain and hidden Markov models at the very center of its examination of current pattern recognition systems, demonstrating how the models can be used in a range of different applications.

Автор: Bishop, Christopher M.
Название: Neural Networks for Pattern Recognition
ISBN: 0198538642 ISBN-13(EAN): 9780198538646
Издательство: Oxford Academ
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Цена: 13939.00 р.
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Описание: This book is the first to provide a comprehensive account of neural networks from a statistical perspective. Its emphasis is on pattern recognition, which currently represents the area of greatest applicability for neural networks. By focusing on pattern recognition, the book provides a much more extensive treatment of many topics than is available in earlier books.

Автор: Sergios Theodoridis
Название: Pattern Recognition,
ISBN: 1597492728 ISBN-13(EAN): 9781597492720
Издательство: Elsevier Science
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Цена: 14483.00 р.
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Описание: Considers classical and theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. This book provides an self-contained volume encapsulating this spectrum of information.

Автор: Kumar
Название: Correlation Pattern Recognition
ISBN: 0521153484 ISBN-13(EAN): 9780521153485
Издательство: Cambridge Academ
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Цена: 8554.00 р.
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Описание: This book provides a needed review of the diverse background material needed for correlation pattern recognition, developing the signal processing theory, the pattern recognition metrics, and the practical application know-how from basic premises. Includes case studies of interest, such as face and fingerprint recognition. For graduate students and practitioners.

Автор: Liu, Zhi-Qiang
Название: Type-2 Fuzzy Graphical Models for Pattern Recognition
ISBN: 3662446898 ISBN-13(EAN): 9783662446898
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition.

Автор: Lars Eld?n
Название: Matrix Methods in Data Mining and Pattern Recognition
ISBN: 0898716268 ISBN-13(EAN): 9780898716269
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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Описание: Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented book describes how modern matrix methods can be used to solve these problems, gives an introduction to matrix theory and decompositions, and provides students with a set of tools that can be modified for a particular application. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problem-solving environments such as MATLAB. In Part II, linear algebra techniques are applied to data mining problems. Part III is a brief introduction to eigenvalue and singular value algorithms. The applications discussed include classification of handwritten digits, text mining, text summarization, pagerank computations related to the Google search engine, and face recognition. Exercises and computer assignments are available on a Web page that supplements the book.

Автор: Mitra Basu; Tin Kam Ho
Название: Data Complexity in Pattern Recognition
ISBN: 1849965579 ISBN-13(EAN): 9781849965576
Издательство: Springer
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Цена: 23058.00 р.
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Описание: The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance.

Автор: Jia Zeng; Zhi-Qiang Liu
Название: Type-2 Fuzzy Graphical Models for Pattern Recognition
ISBN: 3662515229 ISBN-13(EAN): 9783662515228
Издательство: Springer
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Цена: 14365.00 р.
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Описание: This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition.

Автор: Jorge S. Marques; Nicol?s P?rez de la Blanca; Pedr
Название: Pattern Recognition and Image Analysis
ISBN: 3540261532 ISBN-13(EAN): 9783540261537
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Constitutes the proceedings of the Second Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2005, held in Estoril, Portugal in June 2005. This set features papers that are organized in topical sections on computer vision, shape and matching, image and video processing, image and video coding, face recognition, and, robotics.