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Pattern Recognition: Concepts, Methods and Applications [Hardcover]

J.P. Marques de Sá (Author)
4.0 out of 5 stars  See all reviews (1 customer review)


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Book Description

October 2, 2001
The book provides a comprehensive view of Pattern Recognition concepts and methods, illustrated with real-life applications in several areas. It is appropriate as a textbook of Pattern Recognition courses and also for professionals and researchers who need to apply Pattern Recognition techniques. These are explained in a unified an innovative way, with multiple examples enhacing the clarification of concepts and the application of methods. Recent methods and results in Pattern Recognition are also presented in a clear way. A CD-ROM offered with the book includes datasets and software tools, making it easier for the reader to follow the taught matters in a hands-on fashion right from the start.

Editorial Reviews

Review

From the reviews of the first edition: "The book gives an overview about the wide field of pattern recognition. … The book is primarily addressed to undergraduate and graduate students of engineering and computer science courses. It gives a good introduction into the field of clustering and pattern recognition." (Hans-Peter Altenburg, Zentralblatt MATH, Vol. 1009, 2003) "‘Patern Recognition’ presents methods and techniques that are suitable for practical application in areas including robot assisted manufacture, medical diagnostic systems, forecast of economic variables, exploration of Earth’s resources, and satellite data analysis. … This book provides comprehensive, non-specialist coverage of pattern recognition. Although primarily aimed at undergraduate and graduate engineering and computer science students, its clear and practical coverage also makes it suitable for physicians, biologists, geologists and economists." (Assembly Automation, Vol. 22 (4), 2002)

Product Details

  • Hardcover: 318 pages
  • Publisher: Springer; 1 edition (October 2, 2001)
  • Language: English
  • ISBN-10: 3540422978
  • ISBN-13: 978-3540422976
  • Product Dimensions: 9.5 x 6.3 x 0.7 inches
  • Shipping Weight: 1.4 pounds
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #3,331,317 in Books (See Top 100 in Books)

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3 of 3 people found the following review helpful:
4.0 out of 5 stars Pattern Recognition - more than theory, May 28, 2003
By A Customer
This review is from: Pattern Recognition: Concepts, Methods and Applications (Hardcover)
This book is a very good overview to Pattern Recognition.
The book considers the necessary theoretical basics like bayesian theory, feature extraction, clustering, statistical classification, structural pattern rec., neural networks and so on. but also has always a close look to practice. A lot of recent research is included and to each chapter references to literature and exercises are given. At many locations practical hints are given and problems are shown. Also some programs and datasets for practical tests are included. In this way the book says more than many other books which only consider the plain theory. The only things I missed were program sources for a fast start in programing of PR software. It was very helpful.
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Inside This Book (learn more)
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
cork stoppers data, rocks dataset, globular data, cork stoppers problem, stoppers dataset, dimensionality ratio, set error estimate, generalized decision function, quadratic decision function, neural net solutions, intelligent problem solver, icicle plot, uncorrelated features, linear decision functions, discarded features, structural pattern recognition, foetal weight, training set error, misclassified cases, orthonormal transformation, classification matrices, pooled covariance matrix, connectionist structure, test set error, foetal heart rate
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Oporto University, Engineering Faculty, New York, World Scientific Pub, Academic Press, John Wiley, Microsoft Excel, Stepwise Analysis, Handbook of Statistics, North Holland Pub, Practical Guide, Press Inc, Signal Noise, Springer Verlag, Boca Raton, Machine Learning, Rows Observ, Ayres de Campos, Clarendon Press, Faculty of Medicine, Matrix-Computer Methods, Portuguese Escudos, Statistical Learning Theory
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