IN5520 – Digital Image Analysis
Course description
Schedule, syllabus and examination date
Course content
Learning outcome
After this course you´ll:
- have good knowledge on methods for texture analysis and the assumptions behind them.
- have good knowledge of object shape representation and description.
- understand the theory and the linear algebra behind central methods for supervised classification of images, in particular Gaussian classifiers.
- understand the concept of curse-of-dimensionality and can use the theory in practice to carefully choose a subset of features and control the complexity of the classifier robustly.
- know the theory behind central methods for feature selection and linear feature transforms.
Admission to the course
Students admitted at UiO must apply for courses in Studentweb. Students enrolled in other Master's Degree Programmes can, on application, be admitted to the course if this is cleared by their own study programme.
If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures for international applicants.
Recommended previous knowledge
Overlapping courses
- 10 credits overlap with IN9520 – Digital Image Analysis (discontinued).
- 10 credits overlap with INF4300 – Digital image analysis (continued).
- 10 credits overlap with INF9305 – Digital Image Analysis (continued).
- 5 credits overlap with INF9305 – Digital Image Analysis (continued).
Teaching
Examination
Oral or written exam (4 hours) dependent on the number of student.
All mandatory assignments must be approved prior to the exam.
It will also be counted as one of your three attempts to sit the exam for this course, if you sit the exam for one of the following courses: INF4300 – Digital image analysis (continued), INF9305 – Digital Image Analysis (continued), IN9520 – Digital Image Analysis (discontinued)
Examination support material
Language of examination
Grading scale
Resit an examination
More about examinations at UiO
- Use of sources and citations
- How to use AI as a student
- Special exam arrangements due to individual needs
- Withdrawal from an exam
- Illness at exams / postponed exams
- Explanation of grades and appeals
- Resitting an exam
- Cheating/attempted cheating
You will find further guides and resources at the web page on examinations at UiO.