Phys.org  September 16, 2021 Existing technologies lack accuracy and ability to scale to effectively aid disaster relief and recovery. Even today, most wildfire event inspectors visit sites and manually classify building damage using before and after images of the buildings. A team of researchers in the US (Stanford University, California Polytechnic State University) has developed DamageMap, an artificial intelligence-powered post-wildfire building damage classifier. It is a binary classifier. Unlike existing solutions DamageMap relies on post-wildfire images alone by separating the segmentation and classification tasks. The model has an overall accuracy of 98% on the validation set (five wildfire events all […]