Applications of Generative Adversarial Network

Generative Adversarial Network (GAN) is a type of deep learning network that can generate data with similar characteristics as the input real data. These networks take advantage of two interrelated Artificial Neural Networks to create fake data. GAN, which was introduced by Ian Goodfellow in 2014, is considered as one of the most interesting ideas in Machine Learning. Such models are mainly used in image generation, voice generation and video generation. This presentation aims at introducing the structure of GANs and reviewing some of its applications in different areas.