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Pattern Recognition [PR]Summary
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 Lecturer
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