Overview
- A comprehensive yet accessible introduction to the core concepts behind pattern recognition
- Presents the funadmental concepts of supervised and unsupervised classification in an informal treatment, allowing the reader to quickly apply these concepts
- Contains exercises at the end of each chapter, with solutions available to instructors online
- Request lecturer material: sn.pub/lecturer-material
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Table of contents (10 chapters)
Keywords
About this book
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 laterchapters.
This book is suitable for undergraduates and graduates studying pattern recognition and machine learning.
Reviews
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)Authors and Affiliations
About the author
Bibliographic Information
Book Title: Pattern Recognition and Classification
Book Subtitle: An Introduction
Authors: Geoff Dougherty
DOI: https://doi.org/10.1007/978-1-4614-5323-9
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Science+Business Media, LLC, part of Springer Nature 2013
Hardcover ISBN: 978-1-4614-5322-2
Softcover ISBN: 978-1-4939-5335-6
eBook ISBN: 978-1-4614-5323-9
Edition Number: 1
Number of Pages: XI, 196
Number of Illustrations: 54 b/w illustrations, 104 illustrations in colour
Topics: Pattern Recognition, Applications of Nonlinear Dynamics and Chaos Theory, Signal, Image and Speech Processing, Computer Appl. in Life Sciences, Algorithms