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Pattern Recognition An Algorithmic Approach /
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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Springer London : Imprint: Springer,
2011.
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| Edición: | 1st ed. 2011. |
| Colección: | Undergraduate Topics in Computer Science,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 100 | 1 | |a Murty, M. Narasimha. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Pattern Recognition |h [electronic resource] : |b An Algorithmic Approach / |c by M. Narasimha Murty, V. Susheela Devi. |
| 250 | |a 1st ed. 2011. | ||
| 264 | 1 | |a London : |b Springer London : |b Imprint: Springer, |c 2011. | |
| 300 | |a XII, 263 p. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 490 | 1 | |a Undergraduate Topics in Computer Science, |x 2197-1781 | |
| 505 | 0 | |a Introduction -- Representation -- Nearest Neighbour Based Classifiers -- Bayes Classifier -- Hidden Markov Models -- Decision Trees -- Support Vector Machines -- Combination of Classifiers -- Clustering -- Summary -- An Application: Handwritten Digit Recognition. | |
| 520 | |a 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. | ||
| 650 | 0 | |a Computer science. | |
| 650 | 1 | 4 | |a Computer Science. |
| 700 | 1 | |a Devi, V. Susheela. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
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| 776 | 0 | 8 | |i Printed edition: |z 9780857294944 |
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| 830 | 0 | |a Undergraduate Topics in Computer Science, |x 2197-1781 | |
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