Pattern Recognition and Classification: An Introduction PDF Download Ebook. Geoff Dougherty offers complete subjects, fundamental to many of the automated electronic systems in use today. Pattern recognition techniques are concerned with the theory and algorithms of putting abstract objects, e.g., measurements made on physical objects, into categories.
Typically the categories are assumed to be known in advance, although there are techniques to learn the categories (clustering). Methods of pattern recognition are useful in many applications such as information retrieval, data mining, document image analysis and recognition, computational linguistics, forensics, biometrics and bioinformatics.
This text 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.
It starts with a short introduction, where the nomenclature is defined. Analog to digital conversion is briefly discussed with a focus on how it impacts further signal analysis. Commonly used preprocessing methods are then described. 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.
A comprehensive yet accessible introduction to the core concepts behind pattern recognition, this book presents the fundamental concepts of supervised and unsupervised classification in an informal treatment, allowing the reader to quickly apply these concepts. It contains exercises at the end of each chapter, with solutions available to instructors online.
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