Synthetic Data Is A Tool For Improving Training And Accuracy Of Deep Learning Systems

Data has always been a critical requirement for computer systems. Without enough data, testing is not robust. What's important in artificial intelligence applications using deep learning (DL) is not the volume of data for the sake of volume, it's variety. For instance, in training autonomous vehicle systems, there are an unending set of driving scenarios. In facial recognition, too many systems have yet to train with a wide variety of faces.