This book considers classical and current theory and practice, of both supervised and unsupervised pattern recognition, to build a complete background for professionals and students of engineering. Th
Researchers from various disciplines such as pattern recognition, statistics, and machine learning have explored the use of ensemble methodology since the late seventies. Thus, they are faced with a w
Pattern recognition, image processing and computer vision are closely linked areas which have seen enormous progress in the last fifty years. Their applications in our daily life, commerce and industr
This book adopts a detailed and methodological algorithmic approach to explain the concepts of pattern recognition. While the text provides a systematic account of its major topics such as pattern rep
This 2010 handbook is identified as a fourth edition, but it's actually a completely new work and is the fourth in a series of handbooks published in 1993, 1999, and 2005. The 33 chapters are all new.
This book is concerned with a fundamentally novel approach to graph-based pattern recognition based on vector space embedding of graphs. It aims at condensing the high representational power of graphs
The book is a collection of invited chapters by renowned experts and is part of a series on Language Processing, Pattern Recognition, and Intelligent Systems. The content is wide-ranging, encompassing
The book is a collection of invited chapters by experts in Chinese document and text processing, and is part of a series on Language Processing, Pattern Recognition, and Intelligent Systems. The chapt
Support Vector Machines (SVMs) are among the most important recent developments in pattern recognition and statistical machine learning. They have found a great range of applications in various fields
This review volume provides from both theoretical and application points of views, recent developments and state-of-the-art reviews in various areas of pattern recognition, image processing, machine l
Support Vector Machines (SVMs) are among the most important recent developments in pattern recognition and statistical machine learning. They have found a great range of applications in various fields
