Deep Learning Triaging For Disaster Response

One of the early GDELT APIs we created was a special live stream of all coverage worldwide that GDELT monitors about currently active natural disasters. As soon as a disaster is assigned a GLIDE number we begin a live JSON and CSV feed of key selected indicators derived from global media coverage. One of those feeds is a list of all articles about the disaster that contain images, making it possible for aid organizations to triage and better understand the extend and nature of the damage across the affected area. One of the challenges, however, lies in the shear volume and speed of the GDELT firehose, which can easily exceed tens or hundreds of thousands of images for a given disaster. Yet, photographs of presidents at podiums, smiling volunteers, aid trucks, and…

Link to Full Article: Deep Learning Triaging For Disaster Response

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