UnivIS
Informationssystem der Friedrich-Alexander-Universität Erlangen-Nürnberg © Config eG 
FAU Logo
  Sammlung/Stundenplan    Modulbelegung Home  |  Rechtliches  |  Kontakt  |  Hilfe    
Suche:      Semester:   
 
 Darstellung
 
Druckansicht

 
 
 Außerdem im UnivIS
 
Vorlesungs- und Modulverzeichnis nach Studiengängen

Vorlesungsverzeichnis

 
 
Veranstaltungskalender

Stellenangebote

Möbel-/Rechnerbörse

 
 
Internationale Wirtschaftsinformatik / International Information Systems (Master of Science) >>

  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 14:15 - 15:45, H4; Mi 12:15 - 13:45, H5

Studienfächer / Studienrichtungen
WPF MT-MA-BDV 1-3
PF IuK-MA-MMS-INF ab 1
PF IuK-MA-MMS 1-4
WPF CE-MA-TA-IT ab 1
WPF INF-MA ab 1
WPF CME-MA ab 1
WF ASC-MA 1-4

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: 18, Maximale Teilnehmerzahl: 120
www: http://www5.cs.fau.de/lectures/ws-1718/pattern-recognition-pr/

Zugeordnete Lehrveranstaltungen
UE: Pattern Recognition Exercises
Dozentinnen/Dozenten: Sebastian Käppler, M. Sc., AmirAbbas Davari, M. Sc., Dalia Rodriguez Salas, M.Eng.
www: http://www5.cs.fau.de/lectures/ws-1718/pattern-recognition-pr/
UE: Pattern Recognition Programming
Dozentinnen/Dozenten: Sebastian Käppler, M. Sc., AmirAbbas Davari, M. Sc., Dalia Rodriguez Salas, M.Eng.
www: http://www5.cs.fau.de/lectures/ws-1718/pattern-recognition-pr/

Verwendung in folgenden UnivIS-Modulen
Startsemester WS 2017/2018:
Pattern Recognition (PR)
Pattern Recognition Deluxe (PR)

Institution: Lehrstuhl für Informatik 5 (Mustererkennung)
UnivIS ist ein Produkt der Config eG, Buckenhof