Master 2024/2025

Introduction to Computer Vision

Type: Elective course (Math of Machine Learning)

When: 1 year, 2 module

Open to: students of one campus

Language: English

Course Syllabus

Abstract

Computer Vision is one of the most rapidly evolving subfields of Data Science with many applications, e. g. in autonomous driving and healthcare, among others. This course is designed to provide a comprehensive systematic introduction to the field. We'll start with the recognition of some simple object elements such as corners and edges and then proceed to the detection of more complex local features. All major problem statements such as image classification, object detection and segmentation as well as the corresponding classical algorithms will be covered within the course. Finally, we'll briefly introduce convolutional networks and discuss key deep learning architectures for the same set of problems. We'll extensively use Python and CV & image analysis libraries scikit-image and OpenCV during hands-ons and homeworks. The final grade will be calculated using the results of three homeworks (20% each) and the final project (40%).