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 image and signal processing and analysis, and in computer vision. Fundamental concepts of supervised and unsupervised classification are presented in an informal, rather than axiomatic, treatment so that the reader can quickly acquire the necessary background for applying the concepts to real problems. More advanced topics, such as semi-supervised classification, combining clustering algorithms and relevance feedback are addressed in the later chapters. This book is suitable for undergraduates and graduates studying pattern recognition and machine learning.
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The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition.
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Introduction.- Classification.- Nonmetric Methods.- Statistical Pattern Recognition.- Supervised Learning.- Nonparametric Learning.- Feature Extraction and Selection.- Unsupervised Learning.- Estimating and Comparing Classifiers.- Projects
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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 image and signal processing and analysis, and in computer vision. Fundamental concepts of supervised and unsupervised classification are presented in an informal, rather than axiomatic, treatment so that the reader can quickly acquire the necessary background for applying the concepts to real problems. More advanced topics, such as estimating classifier performance and combining classifiers, and details of particular project applications are addressed in the later chapters. This book is suitable for undergraduates and graduates studying pattern recognition and machine learning.
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From the reviews:“The book is a concise introduction to the concepts of pattern recognition and classification. … this book is accessible to mathematicians, computer scientists or biomedical engineers. The material of the book is presented in a very simple and accessible way. The author gives many examples presenting the notations and problems which are considered, so it makes the learning easier. … chapters end up with exercises, which help to consolidate the gained knowledge.” (Krzystof Gdawiec, Zentralblatt MATH, Vol. 1263, 2013)
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A comprehensive yet accessible introduction to the core concepts behind pattern recognitionPresents the funadmental concepts of supervised and unsupervised classification in an informal treatment, allowing the reader to quickly apply these conceptsContains exercises at the end of each chapter, with solutions available to instructors onlineRequest lecturer material: sn.pub/lecturer-material
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Produktdetaljer

ISBN
9781493953356
Publisert
2017-04-30
Utgiver
Vendor
Springer-Verlag New York Inc.
Vekt
3226 gr
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet

Forfatter

Biographical note

Geoff Dougherty is a Professor of Applied Physics and Medical Imaging at California State University, Channel Islands.  He is the Author of Springer's Medical Image Processing, Techniques and Applications