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Vår 2022

FYS-2010 Image Analysis - 10 stp


The course is administrated by

Institutt for fysikk og teknologi

Type of course

The course is available as a singular course. The course is also available to exchange students and Fulbright students.

Course overlap

FYS-262 Digital image processing 9 stp

Course contents

The course introduces fundamental topics in digital image analysis, comprising both mathematical operations on images (image processing) and their use in image understanding and interpretation (computer vision). The course covers mathematical characterization of discrete images, sampling, reconstruction and important image transforms. It teaches image filtering in the spatial and frequency domain covering image enhancements, noise removal, and detection of edge, point and corner features that can be used in vision tasks. It also covers algorithms for object detection and extraction, including thresholding, segmentation and classification. The course describes the evolution from image filtering by convolution with static operators to adaptive processing with convolutional neural networks (CNNs) that learn their filters from data. It gives an introduction to deep learning and training of CNNs for image analysis tasks. The course emphasizes practical exercises. It is relevant for further studies in various fields, such as machine learning, remote sensing (earth observation, space physics, optics, microwaves and ultrasound), automation, robotics, and energy data analytics.

Fundamental knowledge of programming is presupposed.


Application deadline

Applicants from Nordic countries: 1 December

Exchange students and Fulbright students: 1 October


Admission requirements

Admission requirements are generell studiekompetanse + SIVING.

Local admission, application code 9391 - singular courses in engineering sciences. The course is also available to exchange students and Fulbright students.


Objective of the course

Knowledge - The student can:

Skills - The student can:

General competence - The student can:


Language of instruction

The language of instruction is English and all of the syllabus material is in English. Examination questions will be given in English, but may be answered either in English or a Scandinavian language.

Teaching methods

Lectures: 40 hours

Exercises: 40 hours


Assessment

Examination:

Assessment scale: Letter grades A-F. A is the highest grade and F is failed.

There will not be arranged a re-sit exam for this course.


Date for examination

Take-home assignment 2 hand out date 08.04.2022 hand in date 19.05.2022;Shorter electronic take-home exam hand out date 09.06.2022 hand in date 09.06.2022

The date for the exam can be changed. The final date will be announced at your faculty early in May and early in November.