Course
code | CC716 |
credit_hours | 3 |
title | Pattern Recognition |
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prequisites | |
credit hours | 3 |
Description/Outcomes | Pattern recognition techniques are concerned with the theory and algorithms of putting abstract objects, e.g., measurements made on physical objects, into categories. Typically, the categories are assumed to be known in advance, although there are techniques to learn the categories (clustering). Methods of pattern recognition are useful in many applications such as information retrieval, data mining, document image analysis and recognition, computational linguistics, forensics, bio-metrics and bioinformatics. |
arabic Description/Outcomes | |
objectives | To introduce the student to the analysis of difficult data structures, for which no prior models is available in order to be able to grasp basic techniques and learn where to learn more about advanced application-specific techniques. |
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ref. books | - Pattern Classification (2nd. Edition) by R. O. Duda, P. E. Hart and D. Stork, Wiley 2002.
- Pattern Recognition and Machine Learning by C. Bishop, Latest Edition.
- Statistics and the Evaluation of Evidence for Forensic Scientists by C. Aitken and F. Taroni, Wiley, Latest Edition.
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