Synthesizing Training Data for Object Detection Using Generative Adversarial Networks
Object detection is an important tool in computer vision and a popular application of machine learning. One of the main challenges in object detection, and machine learning in general, is acquiring sufficient training data. Many types of data can be hard or expensive to collect and label, or be subject to privacy concerns and regulations such as the General Data Protection Regulation (GDPR). This
