Pattern Recognition: An Algorithmic Approach
โ Scribed by Prof. M. Narasimha Murty, Dr. V. Susheela Devi (auth.)
- Publisher
- Springer-Verlag London
- Year
- 2011
- Tongue
- English
- Leaves
- 274
- Series
- Undergraduate Topics in Computer Science 0
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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.
โฆ Table of Contents
Front Matter....Pages I-XI
Introduction....Pages 1-6
Representation....Pages 7-47
Nearest Neighbour Based Classifiers....Pages 48-85
Bayes Classifier....Pages 86-102
Hidden Markov Models....Pages 103-122
Decision Trees....Pages 123-146
Support Vector Machines....Pages 147-187
Combination of Classifiers....Pages 188-206
Clustering....Pages 207-244
Summary....Pages 245-246
An Application: Handwritten Digit Recognition....Pages 247-254
Back Matter....Pages 255-263
โฆ Subjects
Computer Science, general
๐ SIMILAR VOLUMES
<span>This textbook introduces fundamental concepts, major models, and popular applications of pattern recognition for a one-semester undergraduate course. To ensure student understanding, the text focuses on a relatively small number of core concepts with an abundance of illustrations and examples.
<span>This textbook introduces fundamental concepts, major models, and popular applications of pattern recognition for a one-semester undergraduate course. To ensure student understanding, the text focuses on a relatively small number of core concepts with an abundance of illustrations and examples.
An accompanying manual to Theodoridis/Koutroumbas, Pattern Recognition, that includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition.