Pattern Recognition [PR]
In this lecture the main principles of Pattern Recognition are presented and discussed in detail. After a short introduction, where the nomenclature is defined and some basic procedures are shown, methods used for preprocessing are described. Afterwards several methods for feature extraction and the different approaches (heuristic vs. analytic) are presented as well as procedures for measuring the quality of features and for feature selection. The both basic methods for classification purposes are discussed, numerical and syntactical classification. This will capture statistical, distribution free and nonparametric classification approaches as well as neural networks and grammars. In the tutorials the methods and procedures which are presented in this lecture are illustrated using simple exercises.
Dates & Rooms:
Monday, 10:15 - 11:45; Room: H10
Tuesday, 14:00 - 15:00; Room: H10