Pattern Recognition and Machine Intelligence, Santanu Chaudhury; Sushmita Mitra; C.A. Murthy; P.

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 0387310738 ISBN-13(EAN): 9780387310732
Издательство: Springer
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Цена: 79190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.

Автор: Sergios Theodoridis
Название: Introduction to Pattern Recognition: A Matlab Approach,
ISBN: 0123744865 ISBN-13(EAN): 9780123744869
Издательство: Elsevier Science
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Цена: 37050.00 T
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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: Kumar
Название: Correlation Pattern Recognition
ISBN: 0521153484 ISBN-13(EAN): 9780521153485
Издательство: Cambridge Academ
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Цена: 57030.00 T
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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: Bishop, Christopher M.
Название: Neural Networks for Pattern Recognition
ISBN: 0198538642 ISBN-13(EAN): 9780198538646
Издательство: Oxford Academ
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Цена: 96090.00 T
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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: 96550.00 T
Наличие на складе: Нет в наличии.
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: Petra Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3642030696 ISBN-13(EAN): 9783642030697
Издательство: Springer
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Цена: 121110.00 T
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Описание: 6th International Conference MLDM 2009 Leipzig Germany July 2325 2009 Proceedings. .

Автор: Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319419196 ISBN-13(EAN): 9783319419190
Издательство: Springer
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Цена: 89440.00 T
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Описание: The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.

Автор: Ashish Ghosh; Rajat K. De; Sankar K Pal
Название: Pattern Recognition and Machine Intelligence
ISBN: 3540770453 ISBN-13(EAN): 9783540770459
Издательство: Springer
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Цена: 107130.00 T
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Описание: Constitutes the refereed proceedings of the Second International Conference on Pattern Recognition and Machine Intelligence, PReMI 2007, held in Kolkata, India in December 2007. This book presents 82 revised papers that were reviewed and selected from 241 submissions.

Автор: Brian D. Ripley
Название: Pattern Recognition and Neural Networks
ISBN: 0521717701 ISBN-13(EAN): 9780521717700
Издательство: Cambridge Academ
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Цена: 51750.00 T
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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/