Communications of the ACM
What Deep Learning Reveals About Saturn's Storms
PlanetNet is a new deep learning approach that identifies and maps the components and features in turbulent regions of Saturn's atmosphere.
Credit: NASA/JPL-Caltech/Space Science Institute
Researchers at the University of Arizona and University College London in the U.K. have developed PlanetNet, a deep learning approach that identifies and maps the components and features in turbulent regions of Saturn's atmosphere.
The first demonstration of the PlanetNet algorithm shows the vast regions affected by storms and that dark storm clouds contain material swept up from the lower atmosphere by strong vertical winds.
The researchers trained and tested PlanetNet using infrared data from the Visible and Infrared Mapping Spectrometer instrument on Cassini, a joint mission between the U.S. National Aeronautics and Space Administration (NASA), the European Space Agency, and the Italian Space Agency.
The map produced by PlanetNet shows significant differences between the center of storms and the surrounding areas.
From University of Arizona
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Abstracts Copyright © 2019 SmithBucklin, Washington, DC, USA
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