The main approaches to the preparation of visual data for training neural network algorithms

The paper analyzes the main approaches that developers of neural network algorithms use to prepare training data and form training samples. Possible methods of obtaining marked-up images are considered, including open libraries of marked-up images, specialized image markup editors, synthetic data generators, and a combined approach using GAN networks. The analysis of the main difficulties that arise in the preparation of training data, and ways to overcome them.