Pattern Recognition Course

Slides in English

Contents PDF
1. Introduction and Application Areas chapter 0, chapter 1
2. Basics of Pattern Recognition
(equivalence classes, position invariant feature extraction)
chapter 2a 2b 2c
3. Position Invariant Grayscale Image Detection
(the CT class, parallel implementation, extension to 2-D case, effects of systematic and stochastic noise, clustering properties)
chapter 3a 3b
4. Position Invariant Contour Image Detection
(contour extraction, Fourier analysis, Fourier descriptors for the equivalence class of similarity and affine transformed patterns).
chapter 4a 4b 4c 4d 4e
5. General Approaches for Computing Invariants chapter 5a 5b 5c
6. Feature Reduction, Feature Selection chapter 6
7. The Optimum Classifier, MAP- and MLE-criteria, Metrics chapter 7a 7b 7c
8. Neural Networks chapter 8a 8b
9. The Polynomial Classifier chapter 9
10. Support Vector Machines chapter 10

These slides were created in WS04/05 and are updated from time to time. Please refer to the German slides for latest updates and bug-fixes.