Pattern Recognition

Module Code
PI5012
Module Coordinators
Klaus Rinn
Teachers
Klaus Rinn
Short Description

Hough transformationen and RANSAC, statistical decision theory, Fourier-descriptors, classifiers and learning strategies, neural networks, sequential data analysis, hidden Markov models.

Learning Objectives

The students are familiar with pattern recognition algorithms able to select the most appropriate for their application. They have hands on experience, focused on pattern recognition in images.

Duration in Semester
1
Instruction Language
German
Total Effort
6 CrP; an estimated 180 hours, of which approximately 60 are spent in class.
Weekly School Hours
4
Method of Instruction

Seminaristischer Unterricht 4 SWS

Requirements for the awarding of Credit Points

Prüfungsvorleistung: 2 anerkannte Hausübungen Prüfungsleistung: Klausur

Availability
Yearly
References
  • Vorlesungsfolien
  • Duda, Hart, Stock: Pattern Classification, Wiley
  • Niemann: Pattern Analysis and Understanding, Springer
  • Jähne: Digitale Bildverarbeitung, Springer
  • Abe: Support Vector Machines for Pattern Classification, Springer