Pattern Recognition

The course is a substitute for:

Pattern Recognition and Machine Learning (A4B33RPZ)

Lecturer:

Jiří Matas (gar.)

Tutor:

Jiří Matas (gar.), Martin Dolejší, Andrej Mikulík, Jiří Trefný

Supervisor:

Department of Cybernetics

Synopsis:

The course gives an introduction to statistical and syntactic pattern recognition. The classification (pattern recognition) problem as risk minimization. Bayes decision-making. Parametric classifiers. Learning. Parameter estimation. Non- parametric classifiers. The nearest neighbour method. Neural nets principles. and learning. Testing. Feature selection. Support Vector Machines. Cluster analysis. Structural risk minimization. Syntactic Pattern Recognition. Languages, grammars, automata. Parsing, syntactic classification. Applications of Pattern Recognition.

Requirements:

Syllabus of lectures:

1. Pattern recognition, decision making, formalization

2. Bayes decision making.

3. Non-bayesian problems.

4. Parameter estimation

3. Linear classifier. Support vector machine

4. Perceptron, neural networks. Radial basis functions

5. Clustering. EM algorithm. Unsupervised learning

6. Vapnik´s and other learning theories

7. Adaboost learning.

8. Support vector machines.

9. Neural nets. Learning via backpropagation.

10. Cluser analysis

11. Unsupervised learning, the Expectation-Maximization Algorithm (EM)

12. Sequential decision making - Wald's theory.

13. Feature selection and extraction, principle component analysis, Fisher's linear discriminant

Syllabus of tutorials:

Students solve practical pattern recognition problems such as Optical Character Recognition using a range of learning methods such as Perceptron, Support Vector Machine or Adaboost.

Study Objective:

Study materials:

[1]Duda, Hart, Stork: Pattern Classification, Wiley, 2001

[2] Schlesinger, M.I., Hlaváč, V.: Theory of statistical and structural recognition in 10 lectures, 2002

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Biomedical Engineering- structured studies (compulsory course)