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A course is the basic teaching unit, it's design as a medium for a student to acquire comprehensive knowledge and skills indispensable in the given field. A course guarantor is responsible for the factual content of the course.
For each course, there is a department responsible for the course organisation. A person responsible for timetabling for a given department sets a time schedule of teaching and for each class, s/he assigns an instructor and/or an examiner.
Expected time consumption of the course is expressed by a course attribute extent of teaching. For example, extent = 2 +2 indicates two teaching hours of lectures and two teaching hours of seminar (lab) per week.
At the end of each semester, the course instructor has to evaluate the extent to which a student has acquired the expected knowledge and skills. The type of this evaluation is indicated by the attribute completion. So, a course can be completed by just an assessment ('pouze zápočet'), by a graded assessment ('klasifikovaný zápočet'), or by just an examination ('pouze zkouška') or by an assessment and examination ('zápočet a zkouška') .
The difficulty of a given course is evaluated by the amount of ECTS credits.
The course is in session (cf. teaching is going on) during a semester. Each course is offered either in the winter ('zimní') or summer ('letní') semester of an academic year. Exceptionally, a course might be offered in both semesters.
The subject matter of a course is described in various texts.

NI-ROZ Pattern Recognition Extent of teaching: 2P+1C
Instructor: Haindl M. Completion: Z,ZK
Department: 18101 Credits: 5 Semester: Z

Annotation:
The aim of the module 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. Students will learn the fundamental concepts and methods of pattern recognition, including probability models, parameter estimation, and their numerical aspects.

Lecture syllabus:
1. Elements of pattern recognition.
2. Basic pattern recognition concepts.
3. Bayesian decision theory.
4. Learning theory.
5. Parametric classifiers.
6. Non-parametric classifiers.
7. Support vector machines.
8. Hierarchical classifiers.
9. Pattern recognition using neural networks.
10. Classification quality estimation.
11. Dimensionality reduction.
12. Feature selection.
13. Cluster analysis.

Seminar syllabus:
1. Course project assignment.
2. Consultations.
3. Consultations.
4. Consultations.
5. Consultations.
6. Course project control.
7. Consultations.
8. Consultations.
9. Consultations.
10. Consultations.
11. Consultations.
12. Projects presentation workshop.
13. Projects presentation workshop, assessment.

Literature:
1. Devijver, P. A., Kittler, J. ''Pattern Recognition: A Statistical Approach''. Prentice Hall, 1982. ISBN 0136542360.
2. Duda, R. O., Hart, P. E., Stork, D. G. ''Pattern Classification (2nd Edition)''. Wiley-Interscience, 2000. ISBN 0471056693.
3. Webb, A. R. ''Statistical Pattern Recognition (2nd Edition)''. Wiley, 2002. ISBN 0470845147.
4. Theodoridis, S., Koutroumbas, K. ''Pattern Recognition''. Academic Press, 2008. ISBN 1597492728.

Requirements:
introductory probability, programming, English

Informace o předmětu a výukové materiály naleznete na https://courses.fit.cvut.cz/MI-ROZ/

The course is also part of the following Study plans:
Study Plan Study Branch/Specialization Role Recommended semester
NI-PB.2020 Computer Security V Není
NI-ZI.2020 Knowledge Engineering V Není
NI-SPOL.2020 Unspecified Branch/Specialisation of Study V Není
NI-TI.2020 Computer Science V Není
NI-TI.2023 Computer Science V Není
NI-NPVS.2020 Design and Programming of Embedded Systems V Není
NI-PSS.2020 Computer Systems and Networks V Není
NI-MI.2020 Managerial Informatics V Není
NI-SI.2020 Software Engineering (in Czech) V Není
NI-SP.2020 System Programming V Není
NI-WI.2020 Web Engineering V Není
NI-SP.2023 System Programming V Není


Page updated 29. 3. 2024, semester: L/2021-2, Z,L/2023-4, Z/2021-2, Z/2020-1, Z/2019-20, L/2020-1, Z,L/2022-3, L/2019-20, Send comments to the content presented here to Administrator of study plans Design and implementation: J. Novák, I. Halaška