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Course detail
FSI-RUIAcad. year: 2023/2024
The course consists of two parts. The first part deals with many-valued logic, theory of fuzzy sets and their applications in artificial intelligence. The second part consists of image processing and pattern recognition for applications in technology and science.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Entry knowledge
Rules for evaluation and completion of the course
Course-unit credit based on written test.The exam has a written and oral part.
Attendance at seminars is controlled. An absence can be compensated via solving additional problems.
Aims
The aim of the course is to provide students with information about usage of multi-valued logic in technical applications and with computer image analysis and pattern recognition.
Knowledge of multi-valued logic, fuzzy sets theory, linguistic models and expert systems used in technical applications. Knowledge of image processing, analysis and pattern recognition.
Study aids
Prerequisites and corequisites
Basic literature
Recommended reading
Elearning
Classification of course in study plans
specialization IME , 1 year of study, summer semester, compulsory-optionalspecialization BIO , 1 year of study, summer semester, compulsory-optional
Lecture
Teacher / Lecturer
Syllabus
1. Multi-valued logic, formulas, truth evaluation 2. T-norms, T-conorms, generalized implications 3. Fuzzy sets and operations with them4. Linguistic variables, linguistic models, control systems5. Expert systems based on multi-valued logic6. Classical and digital photography 7. CCD a CMOS technology8. Noise, classification, analysis, filtration9. MTF a PSF, convolution, deconvolution10. Fourier methods of image processing 11. Adaptive filters, image segmentation 12. Classification of objects and pattern recognition 13. Classification of objects and pattern recognition
Computer-assisted exercise