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SRoll3: A neural network approach to reduce large-scale systematic effects in the Planck High Frequency Instrument maps
In the present work, we propose a neural network based data inversion approach to reduce structured contamination sources, with a particular focus on the mapmaking for Planck High Frequency Instrument (Planck-HFI) data and the removal of large-scale systematic effects within the produced sky maps.
Locally-adapted convolution-based super-resolution of irregularly-sampled ocean remote sensing data
Super-resolution is a classical problem in image processing, with numerous applications to remote sensing image enhancement.
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