NDAK15013U Advanced Topics in Image Analysis (ATIA)
Volume 2020/2021
Content
The purpose of this course is to expose the student to selected advanced topics in image analysis. The course will bring the student up to a level sufficient for master thesis work within image analysis and computer vision. Focus is not on specific topics, but rather on recent research trends.
Learning Outcome
Knowledge of
- Selected advanced topics in image analysis.
Skills to
- Read, review and understand recent scientific papers.
- Apply the knowledge obtained by reading scientific papers.
- Compare methods from computer vision and image analysis and assess their potentials and shortcomings.
Competences to
- Understand advanced methods, and to transfer the gained knowledge to solutions to small problems.
- Plan and carry out self-learning.
- Present the result of small assignments in scientific writing.
Literature
See Absalon.
Recommended Academic Qualifications
You should have passed the
courses "Machine Learning"/“Statistical Methods for
Machine Learning” and “Signal and Image Processing”, or similar.
Academic qualifications equivalent to a BSc degree is recommended.
Academic qualifications equivalent to a BSc degree is recommended.
Teaching and learning methods
Lectures and project
work.
Workload
- Category
- Hours
- Lectures
- 14
- Preparation
- 90
- Project work
- 102
- Total
- 206
Feedback form
Written
Oral
Individual
Collective
Continuous feedback during the course of the
semester
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Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Written assignmentThe written assignment is an individual report written during the course.
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
- Re-exam
Same as the ordinary exam.
Criteria for exam assesment
See Learning Outcome.
Course information
- Language
- English
- Course code
- NDAK15013U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 2
- Schedule
- B
- Course capacity
- No limit
- Course is also available as continuing and professional education
- Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Computer Science
Contracting faculty
- Faculty of Science
Course Coordinators
- Søren Ingvor Olsen (6-6c716a79727543676c316e7831676e)
Saved on the
22-06-2020