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AstroSURE: Learning to Remove Noise from Astronomical Images Without Ground Truth Data
Omid Vaheb, Sebastien Fabbro, Stark Draper
In astronomical imaging, the low photon count of exposures necessitates extensive post-processing steps, including contamination removal and denoising. This paper evaluates deep-le…
DanceCam: atmospheric turbulence mitigation in wide-field astronomical images with short-exposure video streams
Spencer Bialek, Emmanuel Bertin, Sébastien Fabbro +4
We introduce a novel technique to mitigate the adverse effects of atmospheric turbulence on astronomical imaging. Utilizing a video-to-image neural network trained on simulated dat…
Probing the Diversity of Type Ia Supernova Light Curves in the Open Supernova Catalog
Chang Bi, Tyrone E. Woods, Sébastien Fabbro
The ever-growing sample of observed supernovae enhances our capacity for comprehensive supernova population studies, providing a richer dataset for understanding the diverse charac…