Automated processing of high resolution airborne images for earthquake damage assessment

6 citations as recorded by crossref.

1. Slope stability and rockfall assessment of volcanic tuffs using RPAS with 2-D FEM slope modelling Á. Török et al. https://doi.org/10.5194/nhess-18-583-2018
2. Multi-Resolution Feature Fusion for Image Classification of Building Damages with Convolutional Neural Networks D. Duarte et al. https://doi.org/10.3390/rs10101636
3. Combined multiscale segmentation convolutional neural network for rapid damage mapping from postearthquake very high-resolution images H. Huang et al. https://doi.org/10.1117/1.JRS.13.022007
4. Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management D. Giordan et al. https://doi.org/10.5194/nhess-18-1079-2018
5. Rapid Identification of Post-Earthquake Collapsed Buildings via Multi-Scale Morphological Profiles With Multi-Structuring Elements B. Wang et al. https://doi.org/10.1109/ACCESS.2020.3007255
6. Fusion of satellite, aircraft, and UAV data for automatic disaster damage assessment M. Kakooei & Y. Baleghi https://doi.org/10.1080/01431161.2017.1294780