Pattern Recognition and Classification: An Introduction Softcover reprint of the original 1st ed. 2013 Edition

Pattern Recognition and Classification: An Introduction Softcover reprint of the original 1st ed. 2013 Edition book cover

Pattern Recognition and Classification: An Introduction Softcover reprint of the original 1st ed. 2013 Edition

Author(s): Geoff Dougherty (Author)

  • Publisher: Springer
  • Publication Date: 30 April 2017
  • Edition: Softcover reprint of the original 1st ed. 2013
  • Language: English
  • Print length: 207 pages
  • ISBN-10: 1493953354
  • ISBN-13: 9781493953356

Book Description

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 laterchapters.

This book is suitable for undergraduates and graduates studying pattern recognition and machine learning.

Editorial Reviews

Review

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)

From the Back Cover

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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