Generating Realistic Blood-Cell Images using Cycle-Consistent Generative Adversial Networks

generative adversial networks are a neural-network based generative models , predominantly used for generating data-samples close to the data distribution they have been trained on .A model for generating realistic blood cell images based on cycle-consistent generative adversial networks is developed along with their corresponding segmentation masks