| GENERAL INFORMATION: | Instructor: Theodorakopoulos Ilias Semester: 9th |
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| CREDITS: | ECTS Units: 3 Teaching Units: 3 Theory Hours: 2 Exercises Hours: 1 Lab Hours: 0 |
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| COURSE PAGE: | https://eclass.duth.gr/courses/TMA354/ | |
Course Description |
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| Introduction to Pattern Recognition Systems. Patterns and Features. Feature Extraction. Classification and recognition of shapes and surfaces with patterns. Statistical methods of pattern recognition based on Bayes Decision Theory. Parameter estimation using Maximum Likelihood and Bayes rule. Non-parametric estimation techniques (Parzen, Nearest Neighbour, Methods of reducing the number of patterns). Linear classifiers. Non-linear classifiers. Neural Networks. Support Vector Machines. Machine Learning. | ||
