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  • Presentation | P31C: Machine Learning and Data Science Methods for Planetary Science II Oral
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  • P31C-07: Characterizing the Color and Structure of Jupiter’s Clouds and Aerosols with Deep Learning
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Author(s):
Emma Dahl, California Institute of Technology (First Author, Presenting Author)
Ramanakumar Sankar, Florida Institute of Technology
Bernadette Bucher, University of Michigan
Aditya Singh, University of Michigan
Shrey Shah, University of Michigan
G. Eichstädt, Independent scholar
Michael Wong, Space Sciences Laboratory
Georgios Georgakis, Jet Propulsion Laboratory, California Institute of Technology


JunoCam, an optical camera on board the Juno spacecraft, was not fully calibrated before launch. Here, we report on efforts to use machine learning to generate models of calibrated JunoCam data that we can then use to study Jupiter's clouds at scales not available to Earth-based telescopes.



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