On the Color Transformation Problem Based on Generative-Adversarial Networks

This paper is devoted to the development of an artificial neural network model that solves the problem of colorization of black-and-white images. A conditional generative- adversarial neural network model is proposed as a solution to the problem. This approach is implemented in Python language using TensorFlow machine learning library in Jupyter Notebook development environment. The performance of the model has been analyzed using selected metrics to evaluate the quality of image generation. The implemented model can be used in automated image processing systems.