Fig. 1 (IMAGE) Osaka University Caption Comparison of manually annotated datasets and automatically generated synthetic datasets. The conventional method requires images to be labeled by hand when the training set is produced, whereas our proposed system can automatically create synthetic data with instance annotations using digital assets from a city digital twin. Credit 2022 Jiaxin Zhang et al., Automatic generation of synthetic datasets from a city digital twin for use in the instance segmentation of building facades, Journal of Computational Design and Engineering Usage Restrictions Credit must be given to the creator. License CC BY Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.