BUILDING SEGMENTATION FROM AIRBORNE VHR IMAGES USING MASK R-CNN

7 citations as recorded by crossref.

1. Quantifying multi-decadal urban growth using Hexagon spy satellite imagery and deep learning building detection across four global cities F. Schug et al. https://doi.org/10.1016/j.landurbplan.2025.105500
2. Building extraction from remote sensing images using deep residual U-Net H. Wang & F. Miao https://doi.org/10.1080/22797254.2021.2018944
3. An enhanced 3D model and generative adversarial network for automated generation of horizontal building mask images and cloudless aerial photographs K. Ikeno et al. https://doi.org/10.1016/j.aei.2021.101380
4. A Large-Scale Multipurpose Benchmark Dataset and Real-Time Interpretation Platform Based on Chinese Rural Buildings W. Deng et al. https://doi.org/10.1109/JSTARS.2024.3386830
5. Mapping and characterising buildings for flood exposure analysis using open-source data and artificial intelligence K. Bhuyan et al. https://doi.org/10.1007/s11069-022-05612-4
6. Automatic Detection of Specific Constructions on a Large Scale Using Deep Learning in Very High Resolution Airborne Imagery P. Achanccaray et al. https://doi.org/10.1007/s41064-023-00237-z
7. Automating the retrospective generation of As-is BIM models using machine learning P. Schönfelder et al. https://doi.org/10.1016/j.autcon.2023.104937