Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used to generate synthetic data that resembles real data by learning from training examples. They find applications in image generation, video synthesis, and data augmentation.
Edge Computing brings computing resources closer to the source of data generation, reducing latency and improving response times. By processing and analysing data locally…