Reseach seminar "Applied tasks of computer vision"

2026/2027

Academic Year

ENG

Instruction in English

6

ECTS credits

Delivered at:

Department of Applied Mathematics and Informatics (Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod))

Course type:

Compulsory course

When:

2 year, 1 module

Instructor

Nikolaeva, Yulia

Course Syllabus

Abstract

The course “Applied tasks of Computer Vision” aims to provide a basic understanding of how to tackle real-world problems. We start with the reminder on the history of computer vision and particularly convolutional neural networks. Then we dive into state-of-the-art architectures of neural networks. We elaborate on how to choose metrics and losses that are suitable for a given task. We show how to utilize widely used frameworks to set-up a pipeline in order to write scalable and reproducible code. We discuss effective and powerful post-processing tools such as uncertainty estimation, active learning, hyperparameters optimization along with classical computer vision tools. By virtue of mentioned techniques one is able to boost models’ performance as well as analyze models’ robustness. Through the course students will approach the solution of a real-world problem utilizing skills and techniques they obtain. After the completion of this course students will have insight of how to solve a problem from its formulation to the deployment of trained models.