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FJH3002 Topics in Computational Brain Science: Vision II 6.0 credits

The subject of this course is to cover one or several timely topics in computational vision at the PhD study level. The choice of topics may vary between different course offerings, depending on the current needs in the PhD education in Computational Brain Science. The course may be given in terms of a supervised reading course, a set of lectures or a combination thereof.

Course offering missing for current semester as well as for previous and coming semesters
Headings with content from the Course syllabus FJH3002 (Spring 2019–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Subjects in the front line of computational vision.

Intended learning outcomes

After the course, the student should be able to:

  • describe, explain and relate basic theories, methodologies and algorithms in computational vision as well as 
  • be able to choose between different types of computational models for a computational implementation of visual operations.

The specific focus of the course may vary from time to time.

Course disposition

The set-up is adapted for each course offering.

Literature and preparations

Specific prerequisites

The student must carry out research at the PhD level within or closely related to computational brain science or vision.

Recommended prerequisites

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Kurslitteraturen bestäms av examinator före varje kurstillfälle.

Selected papers relating to the topic in the front line of computational vision covered by the specific course offering.

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

P, F


  • EXA1 - Examination assignment, 6.0 credits, grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Examination by written homework assignments.

Other requirements for final grade

Approved written report.

Opportunity to complete the requirements via supplementary examination

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Opportunity to raise an approved grade via renewed examination

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Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web FJH3002

Offered by

EECS/Computational Science and Technology

Main field of study

No information inserted

Education cycle

Third cycle

Add-on studies

No information inserted

Postgraduate course

Postgraduate courses at EECS/Computational Science and Technology