Pattern Recognition [electronic resource] : An Algorithmic Approach / by M. Narasimha Murty, V. Susheela Devi.

Murty, M. Narasimha author., Author,
1st ed. 2011.
London : Springer London : Imprint: Springer, 2011.
Computer Science (Springer-11645)
Undergraduate topics in computer science 1863-7310
Undergraduate Topics in Computer Science, 1863-7310
1 online resource (XII, 263 pages)
Computer science.
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Computer Science, general. (search)
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Observing the environment, and recognising patterns for the purpose of decision-making, is fundamental to human nature. The scientific discipline of pattern recognition (PR) is devoted to how machines use computing to discern patterns in the real world. This must-read textbook provides an exposition of principal topics in PR using an algorithmic approach. Presenting a thorough introduction to the concepts of PR and a systematic account of the major topics, the text also reviews the vast progress made in the field in recent years. The algorithmic approach makes the material more accessible to computer science and engineering students. Topics and features: Makes thorough use of examples and illustrations throughout the text, and includes end-of-chapter exercises and suggestions for further reading Describes a range of classification methods, including nearest-neighbour classifiers, Bayes classifiers, and decision trees Includes chapter-by-chapter learning objectives and summaries, as well as extensive referencing Presents standard tools for machine learning and data mining, covering neural networks and support vector machines that use discriminant functions Explains important aspects of PR in detail, such as clustering Discusses hidden Markov models for speech and speaker recognition tasks, clarifying core concepts through simple examples This concise and practical text/reference will perfectly meet the needs of senior undergraduate and postgraduate students of computer science and related disciplines. Additionally, the book will be useful to all researchers who need to apply PR techniques to solve their problems. Dr. M. Narasimha Murty is a Professor in the Department of Computer Science and Automation at the Indian Institute of Science, Bangalore. Dr. V. Susheela Devi is a Senior Scientific Officer at the same institution.
Nearest Neighbour Based Classifiers
Bayes Classifier
Hidden Markov Models
Decision Trees
Support Vector Machines
Combination of Classifiers
An Application: Handwritten Digit Recognition.
Devi, V. Susheela. author., Author,
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10.1007/978-0-85729-495-1 doi
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