Advanced Topics in Image Analysis (ATIA)

Course 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 shortcommings.

 

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.

Lectures and assignment work.

See Absalon.

You should have passed the courses "Machine Learning"/​“Statistical Methods for Machine Learning” and “Signal and Image Processing”, or similar.

Continuous feedback during the course of the semester
ECTS
7,5 ECTS
Type of assessment
Written assignment
The report is written during the course.
Electronic submission of individual written report.
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners
Criteria for exam assessment

See Learning Outcome.

 

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 14
  • Class Instruction
  • 14
  • Preparation
  • 90
  • Project work
  • 88
  • English
  • 206