Satellite Can Track Poverty

According to The Verge, a team of Stanford University researchers has developed a more efficient way to track the poverty of the world. They are also able to see crop conditions on rural farms and illegal deforestation around the world, in hard to reach places. Scientists can do this with the creation of a deep learning algorithm that can recognize signs of poverty through satellite images. How Does It Work? Creating the algorithm involved a dual process called transfer learning. In the first step, researchers build the data with a sensory network of images taken during the day and night. This information includes images of five African countries: Malawi, Uganda, Nigeria, Tanzania, and Rwanda. The model was taught, by using deep learning techniques, to anticipate where lights would be at night, in contrast to those…


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