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Disentangling Jupiter's Complex Atmospheric Processes Through the Application of Machine Learning Methods to JunoCam Data - v0.1
A NASA software catalog entry available for reuse or request.
About this technology
Overview
The software has the following functions: 1) Create training data from JunoCam and Hubble Space Telescope in the form of segments from flattened maps2) Train a deep learning model for photometric calibration of JunoCam3) Provide a set of metrics to evaluate the calibration4) Post process the data by creating global mosaics of the calibrated segments 5) Provide tools to convert the data to PDS compliant formats