INF5860 - Machine Learning for Image Analysis
Schedule, syllabus and examination date
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.
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.
Students admitted at UiO must apply for courses in Studentweb. Students enrolled in other Master's Degree Programmes can, on application, be admitted to the course if this is cleared by their own study programme.
Nordic citizens and applicants residing in the Nordic countries may apply to take this course as a single course student.
If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures for international applicants.
- 10 credits overlap with INF9860 - Machine Learning for Image Analysis
- 5 credits overlap with STK4030 - Statistical Learning: Advanced Regression and Classification
- 5 credits overlap with STK9030 - Statistical Learning: Advanced Regression and Classification
2 hours lectures and 2 hours exercises every week. Mandatory assignments must be completed during the course. Rules for mandatory assignmnets.
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.
Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. 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.