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Pattern Recognition

Contents:

  • Bayesian decision rule
  • Performance assessment in pattern recognition
  • Supervised learning with parametric densities
  • Supervised learning with non-parametric densities, classification
  • Linear decision functions, single-layer perceptron
  • Support vector machines (SVMs)
  • Multi-layer perceptron, neural networks (NNs)
  • Boosting methods
  • Non-supervised learning, clustering

 

Lecturer: Prof. Tim Fingscheidt

Assitant: Maximilian Strake

 

Lecture (ET-NT-102):

Contact hours (SWS): 2 h

Time: Mon 13:15 - 14:45

Location: SN 22.2

Start: 28 Oct 2019

Language: German

 

Seminar (ET-NT-103):

Contact hours (SWS): 2 h (held as block seminar)

Date: is not yet known

Time: 9.00AM - 4.30PM

Location: SN 22.2

Language: German

 

Accompanying material:

The lecture script (pdf document) can be downloaded here. Username and password will be announced in the lecture.

 

 

 

Latest information

No latest information at the moment.

 

 

 

 

Examination

Examination type: oral

 

Date: 02.09.2019

 

Time: on appointment with Mrs. Erichsen-Rua

Location: room 306

Consultation hour (questions about exam): by agreement with Maximilian Strake

 

Information abaut exam:

Registration and appointment arrangement of the examination can be done by e-mail to Eike-Asslo Erichsen-Rua. Please give the following information: name, first name, matriculation number, course of study, semester and e-mail address.

Registration period/deadline: 1.02. 2019


In order to cancel the registration please inform Eike-Asslo Erichsen-Rua and do not forget to inform your faculty.

 
 

Updated: Wednesday, 30 October 2019