Pattern Recognition

• Author : J.P. Marques de Sá
• Publisher : Springer Science & Business Media
• Release : 06 December 2012

The book provides a comprehensive view of pattern recognition concepts and methods, illustrated with real-life applications in several areas. A CD-ROM offered with the book includes datasets and software tools, making it easier to follow in a hands-on fashion, right from the start.

• 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 : Konstantinos Koutroumbas,Sergios Theodoridis
• Publisher : Academic Press
• Release : 26 November 2008

This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition: semi-supervised learning, combining clustering algorithms, and relevance feedback. · Thoroughly developed to include many more worked examples to give greater understanding of the

• 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 : Marsha S. Corrigan
• Publisher : Nova Publishers
• Release : 22 April 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 : Brian D. Ripley
• Publisher : Cambridge University Press
• Release : 22 April 2021

This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.

• Author : Anonim
• Publisher : Unknown
• Release : 22 April 2021

• 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 : Pierre A. Devijver,Josef Kittler
• Publisher : Prentice Hall
• Release : 22 April 1982

• Author : Brett Anderson
• Publisher : Scientific e-Resources
• Release : 14 September 2019

Watching the environment and recognising patterns with the end goal of basic leadership is central to human instinct. This book manages the logical train that empowers comparable observation in machines through pattern recognition, which has application in differing innovation regions-character recognition, picture handling, modern computerization, web looks, discourse recognition, therapeutic diagnostics, target recognition, space science, remote detecting, information mining, biometric recognizable proof-to give some examples. This book is a composition of central subjects in pattern recognition utilizing an algorithmic approach.

• Author : M. Narasimha Murty,V. Susheela Devi
• Publisher : Springer Science & Business Media
• Release : 25 May 2011

Observing the environment and recognising patterns for the purpose of decision making is fundamental to human nature. This book deals with the scientific discipline that enables similar perception in machines through pattern recognition (PR), which has application in diverse technology areas. This book is an exposition of principal topics in PR using an algorithmic approach. It provides a thorough introduction to the concepts of PR and a systematic account of the major topics in PR besides reviewing the vast progress

• Author : Sankar K. Pal,Pal. Amita
• Publisher : World Scientific
• Release : 22 April 2021

This volume, containing contributions by experts from all over the world, is a collection of 21 articles which present review and research material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, syntactic/linguistic, fuzzy-set-theoretic, neural, genetic-algorithmic and rough-set-theoretic to hybrid soft computing, with significant real-life applications. In addition, the book describes efficient soft machine learning algorithms for data mining and knowledge discovery. With a balanced mixture of theory, algorithms and applications, as well as up-to-date

• Author : I. T. Turbovich
• Publisher : Unknown
• Release : 22 April 1970

The recognition of sonic and visual patterns is discussed. Special attention is devoted to the algorithmization of processes for creating signs and arriving at solutions. Also examined are the principles of constructing algorithm-recognition machines, methods of processing descriptions, the evaluation of similarities, and other problems connected with theory and experimentation of pattern recognition. There is a bibliography of 180 titles.

• Author : Jun Shen,Patrick Shen-pei Wang,Tianxu Zhang
• Publisher : World Scientific
• Release : 22 April 2021

A study of multispectral image processing and pattern recognition. It covers: geometric and orthogonal moments; minimum description length method for facet matching; an integrated vision system for ALV navigation; fuzzy Bayesian networks; and more.

• Author : Sameer Singh,Maneesha Singh
• Publisher : Springer Science & Business Media
• Release : 03 August 2007

This book features a collection of articles presented at the 2007 Workshop on Advances in Pattern Recognition, which was organized in conjunction with the 5th International Summer School on Pattern Recognition. It provides readers with the state-of-the-art algorithms in the area of pattern recognition as well as a presentation of the cutting edge applications within the field.