Linear End Nonlinear Methods in Pattern Classification PDF Download
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Author: H. J. Greenberg
Publisher:
ISBN:
Category :
Languages : en
Pages : 307
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Book Description
Author: H. J. Greenberg
Publisher:
ISBN:
Category :
Languages : en
Pages : 307
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Book Description
Author: H. J. Greenberg
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Bilal Barkana
Publisher:
ISBN:
Category : Algebras, Linear
Languages : en
Pages : 196
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Book Description
Author: Richard O. Duda
Publisher: John Wiley & Sons
ISBN: 111858600X
Category : Technology & Engineering
Languages : en
Pages : 680
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Book Description
The first edition, published in 1973, has become a classicreference in the field. Now with the second edition, readers willfind information on key new topics such as neural networks andstatistical pattern recognition, the theory of machine learning,and the theory of invariances. Also included are worked examples,comparisons between different methods, extensive graphics, expandedexercises and computer project topics. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.
Author: Mario Figueiredo
Publisher: Springer Science & Business Media
ISBN: 3540425233
Category : Computers
Languages : en
Pages : 654
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Book Description
This book constitutes the refereed proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2001, held in Sophia Antipolis, France in September 2001. The 42 revised full papers presented were carefully reviewed and selected from 70 submissions. The book offers topical sections on probabilistic models and estimation; image modeling and synthesis; clustering, grouping, and segmentation; optimization and graphs; and shapes, curves, surfaces, and templates.
Author: Pedro Latorre Carmona
Publisher: Springer Science & Business Media
ISBN: 3642365302
Category : Technology & Engineering
Languages : en
Pages : 209
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Book Description
This edited book includes extended and revised versions of a set of selected papers from the First International Conference on Pattern Recognition (ICPRAM 2012), held in Vilamoura, Algarve, Portugal, from 6 to 8 February, 2012, sponsored by the Institute for Systems and Technologies of Information Control and Communication (INSTICC) and held in cooperation with the Association for the Advancement of Artificial Intelligence (AAAI) and Pattern Analysis, Statistical Modelling and Computational Learning (PASCAL2). The conference brought together researchers, engineers and practitioners interested on the areas of Pattern Recognition, both from theoretical and application perspectives.
Author: Francis T. S. Yu
Publisher: Cambridge University Press
ISBN: 9780521465175
Category : Computers
Languages : en
Pages : 460
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Book Description
A comprehensive review of optical pattern recognition techniques and implementations, for graduate students and researchers.
Author: Marcello Pelillo
Publisher: Springer
ISBN: 3319781995
Category : Computers
Languages : en
Pages : 583
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Book Description
This volume constitutes the refereed proceedings of the 11th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2017, held in Venice, Italy, in October/November 2017. The 37 revised full papers were carefully reviewed and selected from 51 submissions. The papers are organized in topical sections on Clustering and Quantum Methods; Motion and Tracking; Image Processing and Segmentation; Color, Shading and Reflectance of Light; Propagation and Time-evolution; and Inference, Labeling, and Relaxation.
Author: Andrew R. Webb
Publisher: John Wiley & Sons
ISBN: 0470854782
Category : Mathematics
Languages : en
Pages : 516
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Book Description
Statistical pattern recognition is a very active area of study andresearch, which has seen many advances in recent years. New andemerging applications - such as data mining, web searching,multimedia data retrieval, face recognition, and cursivehandwriting recognition - require robust and efficient patternrecognition techniques. Statistical decision making and estimationare regarded as fundamental to the study of pattern recognition. Statistical Pattern Recognition, Second Edition has been fullyupdated with new methods, applications and references. It providesa comprehensive introduction to this vibrant area - with materialdrawn from engineering, statistics, computer science and the socialsciences - and covers many application areas, such as databasedesign, artificial neural networks, and decision supportsystems. * Provides a self-contained introduction to statistical patternrecognition. * Each technique described is illustrated by real examples. * Covers Bayesian methods, neural networks, support vectormachines, and unsupervised classification. * Each section concludes with a description of the applicationsthat have been addressed and with further developments of thetheory. * Includes background material on dissimilarity, parameterestimation, data, linear algebra and probability. * Features a variety of exercises, from 'open-book' questions tomore lengthy projects. The book is aimed primarily at senior undergraduate and graduatestudents studying statistical pattern recognition, patternprocessing, neural networks, and data mining, in both statisticsand engineering departments. It is also an excellent source ofreference for technical professionals working in advancedinformation development environments. For further information on the techniques and applicationsdiscussed in this book please visit ahref="http://www.statistical-pattern-recognition.net/"www.statistical-pattern-recognition.net/a
Author:
Publisher:
ISBN:
Category : Weights and measures
Languages : en
Pages : 398
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Book Description
