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  • Pattern Recognition (Mustererkennung)
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    • ⤶ Teaching & Studies
    • ⌂ IfN

Pattern Recognition (Mustererkennung)

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: Marvin Sach


Lecture (ET-NT-102)
Contact hours (SWS): 1.5 h
Start: 18 Apr 2023
Time: Tue 13:15 - 14:45
Location: SN 22.1
Language: English

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 22.1
Language: English

Accompanying material

Latest information and the accompanying material can be found in StudIP.

Latest information

For the participation in the lecture and the seminar, the registration in StudIP is necessary.

Examination

Examination type:  Presence exam

Date:  31.08.2023

Time:  15:30 - 17:00

Entry admission starts at 15:00

Location : ZI 24.2  -  ZI 24.3

Consultation hour (questions about exam): by agreement with Ziyi Xu

Information about exam:

  • Exam is scheduled to last   90 minutes  .
  • The exam will be available in both German and English.
  • The exam is a closed-book exam. Therefore, lecture scripts, notes, communication devices, et al., are NOT allowed during the exam. 
  • Allowed material:
    •   Indelible pens. No pencils, not even for drawing
    • Non-programmable calculator
    • Dividers, Ruler
    • Helper sheet "Basics of Probabilities and Probability Density Functions” (We will provide. Only the provided version printed on colored paper is allowed.)

The exam results are available here:

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