Deep Learning for Computer Vision

Course description

The course aims to present basics knowledge of modern approaches which are used for solving computer vision problems: from descriptions to solutions based on deep convolution networks with hacks and practical examples.

Prerequisites

Basics in neural networks and computer vision

Course tools

Python, caffe, keras

About the lecturer

Dr. Oleksandr Baiev

PhD in mathematical modeling and numerical methods (V.N. Karazin Kharkiv National University) with the focus on applying neural networks for solving problems of radiation physics. Deep learning specialist at Samsung R&D Institute Ukraine (from 2014). Associate professor at Kharkiv University (till 2014), founder of SpinOffHack.