To automatically generate data for training deep convolutional neural network models to segment building facades, researchers used a three-dimensional model and game engine to generate digital city twin synthetic training data. They found that a model trained on these data mixed with some real data was competitive with a model trained on real data alone, revealing the potential of digital twin data to improve accuracy and replace costly manually annotated real data.
Click here for original story, City digital twins help train deep learning models to separate building facades
Source: ScienceDaily