Pattern Recognition (Mustererkennung)

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

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:

Pattern Recognition (Mustererkennung)

Contents

For All Visitors

For Students

Internal Tools

Contact