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Published by Springer-Verlag New York Inc, 2013
ISBN 10: 1493953354 ISBN 13: 9781493953356
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Taschenbuch. Condition: Neu. Pattern Recognition and Classification | An Introduction | Geoff Dougherty | Taschenbuch | xi | Englisch | 2017 | Springer | EAN 9781493953356 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
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Published by Springer New York Apr 2017, 2017
ISBN 10: 1493953354 ISBN 13: 9781493953356
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 208 pp. Englisch.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 conce.
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Published by Springer-Verlag New York Inc., 2017
ISBN 10: 1493953354 ISBN 13: 9781493953356
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Published by Springer, Springer Apr 2017, 2017
ISBN 10: 1493953354 ISBN 13: 9781493953356
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 208 pp. Englisch.
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