Automated method allows rapid analysis of disaster damage to structures

WEST LAFAYETTE, Ind. – Researchers are harnessing “deep learning” algorithms and powerful computer vision technology to dramatically reduce the time it takes for engineers to assess damage to buildings after disasters. In the aftermath of a disaster, engineers descend on the scene and must quickly document damage to structures such as buildings, bridges and pipelines before crucial data are destroyed. This damage from a 2016 earthquake in Taiwan is identified using a new automated system that could dramatically reduce the time it takes for engineers to assess damage to buildings after disasters. The system outlines damage within green boxes for easy reference. (Purdue University image/Alana Wilbee). Download image “These teams of engineers take a lot of photos, perhaps 10,000 images per day, and these data are critical to learn how…


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