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.

See Absalon.

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.
Lectures and project work.
  • Category
  • Hours
  • Lectures
  • 14
  • Preparation
  • 90
  • Project work
  • 102
  • Total
  • 206
Written
Oral
Individual
Collective
Continuous feedback during the course of the semester
Credit
7,5 ECTS
Type of assessment
Written assignment
The 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.