Pattern Recognition

WS 13/14

Mayer

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News

Allgemeines

• The lecture Pattern Recognition II deals with a variety of methods of pattern classification including
• Nearest Neighbor Classification
• Linear Classification
• Support Vector Machines
• Neural Classification
• Stochastic Classification
• In the course part project groups of two persons will work on an implementation of a specific pattern classification method validated on various benchmark data sets.

• Requirements
  • Calculus
  • Basic Statistics
  
  
• Course Material
  • Duda, Hart, Stork: Pattern Classification, 2nd ed., John Wiley & Sons
  • Slides Pattern Recognition II SS 13 (incomplete)

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Helmut A. Mayer
helmut@cosy.sbg.ac.at

Last modified: Oct 22 2013