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Informations- und Kommunikationstechnik (Master of Science) >>

  Pattern Recognition (PR)

Lecturers
Prof. Dr.-Ing. Joachim Hornegger, Dr.-Ing. Stefan Steidl, Dr.-Ing. Andreas Maier

Details
Vorlesung
3 cred.h, certificate, ECTS studies, ECTS credits: 5
geeignet als Schlüsselqualifikation, Sprache Deutsch
Time and place: Mon 15:00 - 15:45, RZ 2.037; Tue 10:30 - 12:00, RZ 2.037

Fields of study
WPF MT-MA-BDV ab 1
PF IuK-MA-MMS-INF ab 1
PF CE-MA-TA-IT ab 1
WPF INF-MA ab 1
WPF CME-MA ab 1

ECTS information:
Title:
Pattern Recognition

Credits: 5

Contents
This lecture gives an introduction into the basic and commonly used classification concepts. First the necessary statistical concepts are revised and the Bayes classifier is introduced. Further concepts include generative and discriminative models such as the Gaussian classifier and Naive Bayes, and logistic regression, Linear Discriminant Analysis, the Perceptron and Support Vector Machines (SVMs). Finally more complex methods like the Expectation Maximization Algorithm, which is used to estimate the parameters of Gaussian Mixture Models (GMM), are discussed.
In addition to the mentioned classifiers, methods necessary for practical application like dimensionality reduction, optimization methods and the use of kernel functions are explained.
Finally, we focus on Independent Component Analysis (ICA), combine weak classifiers to get a strong one (AdaBoost), and discuss the performance of machine classifiers.
In the tutorials the methods and procedures that are presented in this lecture are illustrated using theoretical and practical exercises.

Literature
  • lecture notes
  • Duda R., Hart P. and Stork D.: Pattern Classification

  • Niemann H.: Klassifikation von Mustern

  • Niemann H.: Pattern Analysis and Understanding

Additional information
Keywords: Mustererkennung, Vorverarbeitung, Merkmale, Klassifkation
Expected participants: 32
www: http://www5.informatik.uni-erlangen.de/lectures/ws-1213/pattern-recognition-pr/

Assigned lectures
UE: Pattern Recognition Exercises
Lecturer: Thomas Köhler, M. Sc.
www: http://www5.informatik.uni-erlangen.de/lectures/ws-1213/pattern-recognition-pr/

Verwendung in folgenden UnivIS-Modulen
Startsemester WS 2012/2013:
Pattern Recognition (lecture + exercises) (PR)
Pattern Recognition (lecture only) (PR)

Department: Chair of Computer Science 5 (Pattern Recognition)
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