NDAK15013U Advanced Topics in Image Analysis (ATIA)

Volume 2016/2017

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.  Also, core elements of project work and thesis writing will be covered.

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 shortcommings.
  • Plan and conduct small projects and experiments


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 projects 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.
Lectures and project work.
  • Category
  • Hours
  • Class Instruction
  • 14
  • Lectures
  • 14
  • Preparation
  • 90
  • Project work
  • 88
  • Total
  • 206
7,5 ECTS
Type of assessment
Written assignment, prepared throughout the course
Electronic submission of individual written project assignment.
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners

Resubmission of written project assignment.

Criteria for exam assesment

To obtain the grade 12 the student must be able to:

1.    Document understanding of the assignments including the relevant litterature and/or other materials needed for conducting the assignment.
2.    Document solutions to the assignment, including a discussion of the chosen alternatives.
3.    Document any experiments made and any drawn conclusion.