Pattern Recognition and Machine Learning

• Author : Christopher M. Bishop
• Publisher : Springer Verlag
• Release : 17 August 2006

This is the first text on pattern recognition to present the Bayesian viewpoint, one that has become increasing popular in the last five years. It presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It provides the first text to use graphical models to describe probability distributions when there are no other books that apply graphical models to machine learning. It is also the first four-color book on pattern recognition. The book

• Author : J. P. Marques de Sá
• Publisher : Springer Science & Business Media
• Release : 24 September 2021

CD-ROM contains: Datasets -- Software tools.

• Author : Geoff Dougherty
• Publisher : Springer Science & Business Media
• Release : 28 October 2012

The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in

• Author : Julius T. Tou,Rafael C. Gonzalez
• Publisher : Unknown
• Release : 24 September 1977

Decision functions. Pattern classification by distance functions. Pattern classification by likelihood functions. Trainable pattern classifiers-the deterministic approach. Trainable pattern classifiers - the statistical approach. Pattern preprocessing and feature selection. Syntatic pattern recognition. Bibliography. Index.

• Author : Sergios Theodoridis,Konstantinos Koutroumbas
• Publisher : Elsevier
• Release : 07 April 2006

Pattern recognition is a fast growing area with applications in a widely diverse number of fields such as communications engineering, bioinformatics, data mining, content-based database retrieval, to name but a few. This new edition addresses and keeps pace with the most recent advancements in these and related areas. This new edition: a) covers Data Mining, which was not treated in the previous edition, and is integrated with existing material in the book, b) includes new results on Learning Theory and

• Author : William Gibson
• Publisher : Penguin UK
• Release : 24 June 2004

One of the most influential and imaginative sci-fi writers turns his attention to London - with dazzling results. 'Part-detective story, part-cultural snapshot . . . all bound by Gibson's pin-sharp prose' Arena ________________________ Cayce Pollard owes her living to her pathological sensitivity to logos. In London to consult for the world's coolest ad agency, she finds herself catapulted, via her addiction to a mysterious body of fragmentary film footage, uploaded to the Web by a shadowy auteur, into a global quest for this unknown "

• Author : Katrin Franke,Klaus-Robert Müller,Bertram Nickolay,Ralf Schäfer
• Publisher : Springer Science & Business Media
• Release : 11 September 2006

This book constitutes the refereed proceedings of the 28th Symposium of the German Association for Pattern Recognition, DAGM 2006. The book presents 32 revised full papers and 44 revised poster papers together with 5 invited papers. Topical sections include image filtering, restoration and segmentation, shape analysis and representation, recognition, categorization and detection, computer vision and image retrieval, machine learning and statistical data analysis, biomedical data analysis, and more.

• Author : Christopher M. Bishop
• Publisher : Oxford University Press
• Release : 23 November 1995

`Readers will emerge with a rigorous statistical grounding in the theory of how to construct and train neural networks in pattern recognition' New Scientist

• Author : Cornelius T. Leondes
• Publisher : Elsevier
• Release : 09 February 1998

Image Processing and Pattern Recognition covers major applications in the field, including optical character recognition, speech classification, medical imaging, paper currency recognition, classification reliability techniques, and sensor technology. The text emphasizes algorithms and architectures for achieving practical and effective systems, and presents many examples. Practitioners, researchers, and students in computer science, electrical engineering, andradiology, as well as those working at financial institutions, will value this unique and authoritative reference to diverse applications methodologies. Coverage includes: Optical character recognition Speech classification

• Author : James C. Bezdek
• Publisher : Springer Science & Business Media
• Release : 13 March 2013

The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question of whether or not a group of objects form a cluster. A pioneering application of the theory of fuzzy sets to cluster analysis was made in 1969 by Ruspini. It was not until 1973,

• Author : Marsha S. Corrigan
• Publisher : Nova Publishers
• Release : 24 September 2021

Pattern recognition is the research area that studies the operation and design of systems that recognise patterns in data. It encloses subdisciplines like discriminant analysis, feature extraction, error estimation, cluster analysis (together sometimes called statistical pattern recognition), grammatical inference and parsing (sometimes called syntactical pattern recognition). Important application areas are image analysis, character recognition, speech analysis, man and machine diagnostics, person identification and industrial inspection. This book presents leading-edge research from around the world.

• Author : Flasinski Mariusz
• Publisher : World Scientific
• Release : 25 March 2019

This unique compendium presents the major methods of recognition and learning used in syntactic pattern recognition from the 1960s till 2018. Each method is introduced firstly in a formal way. Then, it is explained with the help of examples and its algorithms are described in a pseudocode. The survey of the applications contains more than 1,000 sources published since the 1960s. The open problems in the field, the challenges and the determinants of the future development of syntactic pattern recognition are discussed.

• Author : Chi Hau Chen
• Publisher : World Scientific
• Release : 15 December 2015

Pattern recognition, image processing and computer vision are closely linked areas which have seen enormous progress in the last fifty years. Their applications in our daily life, commerce and industry are growing even more rapidly than theoretical advances. Hence, the need for a new handbook in pattern recognition and computer vision every five or six years as envisioned in 1990 is fully justified and valid.The book consists of three parts: (1) Pattern recognition methods and applications; (2) Computer vision and image processing;

• Author : Richard O. Duda,Peter E. Hart,David G. Stork
• Publisher : John Wiley & Sons
• Release : 09 November 2012

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 : Y. Anzai
• Publisher : Elsevier
• Release : 02 December 2012

This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.