Selected Topics in Pattern Recognition

Lecturer:

Jiří Matas (gar.)

Tutor:

Jiří Matas (gar.)

Supervisor:

Department of Cybernetics

Synopsis:

Prerequisites: basic course in pattern recognition (e.g. P33ROD, 33RPZ).

Selected topics: Anderson's problem, Kozince algorithm, kernel perceptron,

nonlinear Fisher discriminant. Vapnik's learning theorz. Deterministic

learning. Unsupervised learning: Robbins algorithm and emprirical Bayesian

approach. Expectation-minimization algorithm. Recognition of sequences and

directed acyclic graphs. Markov models. Combination of weak classifiers:

boosting and bagging. AdaBoost.

Requirements:

Syllabus of lectures:

Syllabus of tutorials:

Study Objective:

Study materials:

Duda, Richard O.; Hart, Peter E.; Stork, David G.: Pattern Classification,

John Wiley, 2001

Note:

Time-table for winter semester 2011/2012:

Time-table is not available yet

Time-table for summer semester 2011/2012:

	06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon
Tue
Fri	roomKN:G-205 Matas J. 14:30–16:00 (lecture parallel1) Karlovo nám. Laboratoř PC
Thu
Fri

The course is a part of the following study plans:

• Doctoral studies, daily studies (compulsory elective course)
• Doctoral studies, combined studies (compulsory elective course)
• Doctoral studies, structured daily studies (compulsory elective course)
• Doctoral studies, structured combined studies (compulsory elective course)