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Course info
KKY / MPV
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Course description
Department/Unit / Abbreviation
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KKY
/
MPV
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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Title
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Computer Vision Methods
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Form of course completion
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Exam
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Form of course completion
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Exam
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Accredited / Credits
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Yes,
6
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
3
[Hours/Week]
Tutorial
2
[Hours/Week]
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Course credit prior to examination
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Yes
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Course credit prior to examination
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Yes
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Included in study average
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YES
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Language of instruction
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Czech
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Occ/max
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Summer semester
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0 / -
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0 / -
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0 / -
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Included in study average
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YES
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Winter semester
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0 / -
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11 / -
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0 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Winter semester
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Semester taught
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Winter semester
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Minimum (B + C) students
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1
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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Czech
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
1|2|3|4 |
Periodicity |
každý rok
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Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
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Fundamental theoretical course |
No
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Fundamental course |
Yes
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Fundamental theoretical course |
No
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Evaluation scale |
1|2|3|4 |
Evaluation scale for credit before examination |
S|N |
Substituted course
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None
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Preclusive courses
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N/A
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Prerequisite courses
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N/A
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Informally recommended courses
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N/A
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Courses depending on this Course
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N/A
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Histogram of students' grades over the years:
Graphic PNG
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XLS
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Course objectives:
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Understand to the advanced principles of computer vision. Analyze of image information properties and interpret of such information, design and create an advanced algorithm of computer vision with the aim of recognition of objects, phenomena, or scene properties contained in image.
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Requirements on student
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active presence at seminars
project in teams of max 2, project defense,
oral exam
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Content
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Definition of the computer vision task. Advanced methods of representation of image information. Advanced methods of image pre-processing - point brightness transformations, geometric transformations, noise filtration, greadient operators, frequency analysis. Morphologic tranformations. Advanced methods of segmentation. Advanced methods of description of objects - description based on region boundaries, description based on shape of regions. Advanced methods of classification. Advanced methods of motion analysis. Advanced methods of 3D imaging. Applications of computer vision methods in photography, industry, human-computer communication, and medicine.
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Activities
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Fields of study
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Guarantors and lecturers
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Guarantors:
Doc. Ing. Miloš Železný, Ph.D. (100%),
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Lecturer:
Ing. Marek Hrúz, Ph.D. (100%),
Doc. Ing. Miloš Železný, Ph.D. (100%),
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Tutorial lecturer:
Ing. Ivan Gruber, Ph.D. (100%),
Ing. Miroslav Hlaváč, Ph.D. (100%),
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Literature
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
Analysis and interpretation of informations, algorithmization and implementation of tasks, assessment of achieved results. |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
Ability to analyze, research, and generalize presented principles, describe problem domain, compile algorithmization |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Oral exam |
Skills demonstration during practicum |
Project |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture |
Practicum |
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