Machine Learning 1

It is not possible to register for the course 01SU1 if the student is concurrently registered for or has already completed the course 01ROZP2 (mutually exclusive courses).

It is not possible to register for the course 01SU1 if the student is concurrently registered for or has previously completed the course 01ROZP2 (mutually exclusive courses).

Garant předmětu:

Jan Flusser

Lecturer:

Jan Flusser

Tutor:

Jan Flusser

Supervisor:

Department of Mathematics

Synopsis:

[1] features for description and recognition of 2-D shapes

[2] invariant features, Fourier descriptors, moment invariants, differential invariants

[3] statistical pattern recognition, supervised and nonsupervised classification, NN- classifier, linear classifier, Bayessian classifier

[4] clustering in a feature space, iterative and hierarchical methods

[5] dimensionality reduction of a feature space

Requirements:

Syllabus of lectures:

Syllabus of tutorials:

Study Objective:

Study materials:

Key references:

[1] Duda R.O. et al., Pattern Classification, (2nd ed.), John Wiley, New York, 2001

[2] J. Flusser, T. Suk, B. Zitova: 2D and 3D Image Analysis by Moments 1st Edition, Wiley &Sons Ltd., 2016

Recommended references:

[3] Pratt W. K.: Digital Image Processing (3rd ed.), John Wiley, New York, 2001

[4] J. Flusser, T. Suk, B. Zitová, Moments and Moment Invariants in Pattern Recognition, Wiley &Sons Ltd., 2009

Note:

Time-table for winter semester 2023/2024:

Time-table is not available yet

Time-table for summer semester 2023/2024:

Time-table is not available yet

The course is a part of the following study plans:

• Jaderné inženýrství - Aplikovaná fyzika ionizujícího záření (elective course)
• Matematická informatika (compulsory course in the program)
• Fyzikální elektronika - Počítačová fyzika (elective course)