EDB-HSTEU-Net : Earthquake-damaged building detection using a novel hybrid swin transformer efficient U-Net (HSTEU-Net) and transfer learning techniques from post-event VHR remote sensing data
Rapid and accurate generation of building damage maps (BDMs) following earthquakes is crucial for effective disaster response and rescue operations. With the increasing availability of optical very high-resolution remote sensing (OVHR-RS) images, two considerable deep learning challenges arise: (1) developing robust models for data-rich regions and (2) adapting pre-trained models for areas with li