Pattern Recognition 1

Course Code:
11RZ1
Academic Degree:
master
Study Programme:
Technology in Transportation and Telecommunications (N 3710)
semesterlanguagestudy field / specialization
2czech, englishIS Intelligent Transport Systems - 3711T004
Erasmus:
course for Erasmus and Exchange students in summer semester
Form of Study:
full-time
Credits:
3
Number of Hours:
2 + 1 hours per week - in full-time study
Type of Course:
obligatory
Course Completion:
credit, exam
Course Tutor:
 
roh  Lectures:
prof. Ing. Michal Haindl, DrSc.
roh  Training Course:
prof. Ing. Michal Haindl, DrSc.
Supervising Department:
Department of Applied Mathematics (16111)
Keywords:
pattern recognition, classification, segmentation, feature selection, learning
Abstract:
Elements of pattern recognition. Basic PR concepts. Bayesian decision theory. Learning theory. Parametric classifiers. Context classifiers. Classification quality estimation. Vector support machines. Non-parametric classifiers. Feature selection. Cluster analysis.
Objectives:
The main aim of the course is to give a systematic account of the major topics in pattern recognition with emphasis on problems and applications of the statistical approach to pattern recognition. Basic concepts and methods of pattern recognition, incl. machine perception, probability models and computations, parameter estimation will be instructed.