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.
Springer-Verlag New York
|Country of origin:
||235 x 155 x 17mm (L x W x T)
• Online resource
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