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Detecting Change With Artificial Intelligence

机译:用人工智能检测变化

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摘要

In a project for the Defense Department's Defense Innovation Unit (DIU), computer scientists have turned to artificial intelligence and aerial imagery to construct a detailed damage assessment solution. The tool can be used remotely and automatically to determine the amount of damage to buildings and structures from a natural disaster or catastrophe. The prototype, known as the xView Ⅱ model, was tested this fall, with the goal of rolling out a more finalized operational version next year. In the last few years, the U.S. military has seen an enormous amount of weather-related damage to some of its facilities, including the destruction at Tyndall Air Force Base, Florida, from Hurricane Michael in 2018; extensive water damage at Camp Lejeune, North Carolina, from Hurricane Florences torrential rains in 2018; and flooding of the Missouri River and area creeks that impacted one-third of Offutt Air Force Base, Nebraska, in 2019. Meanwhile, this fall, California's wildfires raged over 4 million acres causing irreparable damage, while repeated hurricanes barraged the Gulf Coast.
机译:在国防部的国防创新单位(DIU)的项目中,计算机科学家已经转向人工智能和空中图像,以构建一个详细的伤害评估解决方案。该工具可远程使用,自动使用,以确定对自然灾害或灾难的建筑物和结构的损坏量。这一秋季测试了称为XViewⅡ型号的原型,目前明年推出更加最终的操作版本。在过去的几年里,美国军队对其一些设施造成了大量的天气有关的损害,包括2018年飓风迈克尔·佛罗里达州廷德尔空军基地的破坏;北卡罗来纳州伦敦央町的广泛用水损坏,来自2018年飓风洪水暴雨;密苏里河和地区小溪的洪水影响了2019年内布拉斯加州的三分之一的空军基地。与此同时,加州的野火造成了400多万亩,造成无法弥补的伤害,而重复的飓风阻碍了墨西哥湾沿岸。

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  • 来源
    《Signal》 |2020年第4期|41-43|共3页
  • 作者

    KIMBERLY UNDERWOOD;

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