INF9860 – Machine Learning for Image Analysis
Course description
Schedule, syllabus and examination date
Course content
The course gives an introduction to the theory behind central machine learning algorithms and how these are used in image analysis. Selected methods and tools for deep learning are also presented.
Learning outcome
After this course
- You have good knowledge about the theory behind central classification algorithms, logistic regression, and neural nets and how these are applied to images.
- You are familiar with central mathematical method applied in the algorithms.
- You can discuss and evaluate how different feature extraction methods affect the classification error rate.
- You have knowledge about overtraining, generalization, and validation.
- You know how convolutional networks work and how they can be adapted to various applications.
- You have experience in using tools for deep learning like Tensorflow.
- You have studied selected papers on deep learning.
Admission
PhD candidates from the University of Oslo should apply for classes and register for examinations through Studentweb.
If a course has limited intake capacity, priority will be given to PhD candidates who follow an individual education plan where this particular course is included. Some national researchers’ schools may have specific rules for ranking applicants for courses with limited intake capacity.
PhD candidates who have been admitted to another higher education institution must apply for a position as a visiting student within a given deadline.
Overlapping courses
- 10 credits overlap with INF5860 – Machine Learning for Image Analysis (continued)
- 5 credits overlap with STK4030 – Statistical Learning: Advanced Regression and Classification (discontinued)
- 5 credits overlap with STK9030 – Statistical Learning: Advanced Regression and Classification (discontinued)
Teaching
2 hours lectures and 2 hours exercises every week. Mandatory assignments must be completed during the course. Rules for mandatory assignmnets.
Examination
Written (4 hours) examination. If there are few students the exam will be given as an oral exam. All mandatory assignments have to be accepted in order to take the exam.
Examination support material
No examination support material is allowed.
Language of examination
You may write your examination paper in Norwegian, Swedish, Danish or English.
Grading scale
Grades are awarded on a pass/fail scale. Read more about the grading system.
Explanations and appeals
Resit an examination
Students who can document a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester.
Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.
Withdrawal from an examination
It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt.
Special examination arrangements
Application form, deadline and requirements for special examination arrangements.