The field of pattern recognition has emerged as one of the most
challenging and important endeavours in the area of information
technology research. Research in the area of pattern recognition
has benefits for improving many areas of human endeavour, including
medicine, the economy, the environment, and security. This book
presents some of the latest advances in the area of pattern
recognition theory and applications. The first half of the book
discusses novel pattern classification and matching schemes, and
the second half describes the application of novel tools in
biometrics and digital multimedia. The applications included, such
as face/iris recognition, handwriting recognition, surveillance,
human dynamics, sensor fusion, etc., provide a detailed insight
into how to build real pattern recognition systems and how to
evaluate them. Given the dynamic nature of technology evolution in
this area, this book provides the latest algorithms and concepts
that can be used to build real systems. Features and topics:
Provides state-of-the art algorithms, as well as presents
cutting-edge applications within the field Introduces achievements
in theoretical pattern recognition, including statistical and
Bayesian pattern recognition, structural pattern recognition,
neural networks, classification and data mining, evolutionary
approaches to optimisation, and knowledge based systems Offers
insights and support to practitioners concerned with the
state-of-the art technology in the area Progress in Pattern
Recognition addresses the needs of postgraduate students,
researchers, and practitioners in the areas of computer science,
engineering and mathematicswhere pattern recognition techniques are
widely used. Professor Sameer Singh is Director of the Research
School of Informatics, Loughborough University, UK, and serves as
Editor-in-Chief of the Springer journal, Pattern Analysis and
Applications.
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