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Pattern Recognition (PR)
- Dozent/in
- Prof. Dr.-Ing. Elmar Nöth
- Angaben
- Vorlesung
3 SWS, Schein, ECTS-Studium, ECTS-Credits: 3,75
geeignet als Schlüsselqualifikation, Sprache Englisch
Zeit und Ort: Mo 10:15 - 11:45, H4; Di 14:15 - 15:45, C2 - Chemikum
ab 15.10.2019
- Studienfächer / Studienrichtungen
- WPF MT-MA-BDV 1-3
PF IuK-MA-MMS-INF ab 1
PF ICT-MA-MPS 1-4
WPF CE-MA-INF ab 1
WPF INF-MA ab 1
WPF CME-MA ab 1
WF ASC-MA 1-4
- Voraussetzungen / Organisatorisches
- Please note:
All participants should register in StudOn under "Pattern Recognition
WS2019/20".
The first class on Oct. 14, 2019, will not take place due to introductory
events for the first semester Bachelor students.
- ECTS-Informationen:
- Title:
- Pattern Recognition
- Credits: 3,75
- 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
- Zusätzliche Informationen
- Schlagwörter: Mustererkennung, maschinelle Klassifikation
Erwartete Teilnehmerzahl: 26, Maximale Teilnehmerzahl: 150
www: http://www5.cs.fau.de/lectures/ws-1920/pattern-recognition-pr/
- Zugeordnete Lehrveranstaltungen
- UE: Pattern Recognition Exercises
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Dozentinnen/Dozenten: Stephan Seitz, M. Sc., Dalia Rodriguez Salas, M.Eng.
www: http://www5.cs.fau.de/lectures/ws-1920/pattern-recognition-pr/
- UE: Pattern Recognition Programming
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Dozentinnen/Dozenten: Lina Felsner, M. Sc., Dalia Rodriguez Salas, M.Eng.
www: http://www5.cs.fau.de/lectures/ws-1920/pattern-recognition-pr/
- Verwendung in folgenden UnivIS-Modulen
- Startsemester WS 2019/2020:
- Pattern Recognition (PR)
- Pattern Recognition Deluxe (PR)
- Institution: Lehrstuhl für Informatik 5 (Mustererkennung)
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