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Reproducible Research in Pattern Recognition, Bertrand Kerautret; Miguel Colom; Pascal Monasse


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Автор: Bertrand Kerautret; Miguel Colom; Pascal Monasse
Название:  Reproducible Research in Pattern Recognition
ISBN: 9783319564135
Издательство: Springer
Классификация:




ISBN-10: 3319564137
Обложка/Формат: Paperback
Страницы: 179
Вес: 0.28 кг.
Дата издания: 05.04.2017
Серия: Image Processing, Computer Vision, Pattern Recognition, and Graphics
Язык: English
Издание: 1st ed. 2017
Иллюстрации: 88 illustrations, black and white; x, 179 p. 88 illus.
Размер: 235 x 156 x 10
Читательская аудитория: Professional & vocational
Основная тема: Computer Science
Подзаголовок: First International Workshop, RRPR 2016, Canc?n, Mexico, December 4, 2016, Revised Selected Papers
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Reproducible Research in Pattern Recognition, RRPR 2016, held in Cancun, Mexico, in December 2016. The 12 revised full papers, among them 2 invited talks, presented were carefully reviewed and selected from 16 submissions.


Neural Networks for Pattern Recognition

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.

Pattern Recognition,

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.

Pattern Recognition and Neural Networks

Автор: Brian D. Ripley
Название: Pattern Recognition and Neural Networks
ISBN: 0521717701 ISBN-13(EAN): 9780521717700
Издательство: Cambridge Academ
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Цена: 7762.00 р.
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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/

Introduction to Pattern Recognition: A Matlab Approach,

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: 5557.00 р.
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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.

Correlation Pattern Recognition

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.

Matrix Methods in Data Mining and Pattern 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.

Advances in Feature Selection for Data and Pattern Recognition

Автор: Urszula Sta?czyk; Beata Zielosko; Lakhmi C. Jain
Название: Advances in Feature Selection for Data and Pattern Recognition
ISBN: 3319675877 ISBN-13(EAN): 9783319675879
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of recent advances. The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions and new applications.

Pattern Recognition and Machine Intelligence

Автор: B. Uma Shankar; Kuntal Ghosh; Deba Prasad Mandal;
Название: Pattern Recognition and Machine Intelligence
ISBN: 3319698990 ISBN-13(EAN): 9783319698991
Издательство: Springer
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Цена: 12577.00 р.
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Описание: This book constitutes the proceedings of the 7th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2017,held in Kolkata, India, in December 2017. The total of 86 full papers presented in this volume were carefully reviewed and selected from 293 submissions.

Pattern Recognition

Автор: Fred A. Hamprecht; Christoph Schn?rr; Bernd J?hne
Название: Pattern Recognition
ISBN: 3540749330 ISBN-13(EAN): 9783540749332
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Contains sections on image filtering, restoration and segmentation, shape analysis and representation, and recognition. This book also covers categorization and detection, computer vision and image retrieval, machine learning and statistical data analysis, biomedical data analysis, motion analysis and tracking, and pose recognition.

Soft Computing Approach to Pattern Classification and Object Recognition

Автор: Kumar S. Ray
Название: Soft Computing Approach to Pattern Classification and Object Recognition
ISBN: 1489990100 ISBN-13(EAN): 9781489990105
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Soft Computing Approach to Pattern Classification and Object Recognition establishes an innovative, unified approach to supervised pattern classification and model-based occluded object recognition.

Scalable Pattern Recognition Algorithms

Автор: Pradipta Maji; Sushmita Paul
Название: Scalable Pattern Recognition Algorithms
ISBN: 3319056298 ISBN-13(EAN): 9783319056296
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models.

Graph-Based Representations in Pattern Recognition

Автор: Cheng-Lin Liu; Bin Luo; Walter G. Kropatsch; Jian
Название: Graph-Based Representations in Pattern Recognition
ISBN: 3319182234 ISBN-13(EAN): 9783319182230
Издательство: Springer
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Цена: 7826.00 р.
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Описание: The accepted papers cover diverse issues of graph-based methods and applications, with 7 in graph representation,15 in graph matching, 7 in graph clustering and classification, and 7 in graph-based applications.


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