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Basics in computer vision

Andrey Savchenko, Alexander Smorkalov, Alexander Demidovskij, Anastasiia Sokolova, Vasily Shamporov, Egor Churaev, Valeriy Kalyagin, and Sergey Slashchinin

This Specialization is part of HSE University Master of Computer Vision degree program. Learn more about the admission into the program here and how your Coursera work can be leveraged if accepted into the program. This specialization is intended for a wide range of specialists who want to start getting acquainted with the direction of Computer Vision. In the frame of the specialization, students can organize their mathematical and programming skills necessary for the development of algorithms in the field of Computer vision, as well as learn how to use the OpenCV library for analyzing two-dimensional images. The OpenCV library is widely used by computer vision application developers, so students will be able to apply the skills acquired in this specialization in their real practical activities.

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What's inside

Three courses

2D image processing

(0 hours)

The course covers the use of OpenCV in 2D image processing, including image filtering, thresholding, edge/corner/interest point detection, local and global descriptors, and video tracking.

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Object-oriented programming

(0 hours)

This course introduces OOP in the context of C++. It covers the advantages and features of OOP over procedural programming, and familiarizes students with the standard template library and CMake.

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Mathematics for computer vision

(0 hours)

The course systematizes the mathematical background for computer vision, including sections of mathematical analysis, probability theory, and linear algebra.

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Time

82 hours

Via

Coursera

Institution

HSE University

Instructors

Andrey Savchenko

Alexander Smorkalov

Alexander Demidovskij

Anastasiia Sokolova

Vasily Shamporov

Egor Churaev

Valeriy Kalyagin

Sergey Slashchinin

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