DOE OSTI · 1989920
DeepBench: A simulation package for physical benchmarking data
Abstract
We introduce **DeepBench**, a python library that generates simple simulated image data from first principles, such as basic geometric shapes and astronomical objects. These data are highly valuable for developing (calibration, testing, and benchmarking) statistical and machine learning models because they make it possible to connect the final data product to physically interpretable inputs. This software includes tools to curate and store the datasets to maximize reproducibility.
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Voetberg, M. [Fermilab] (ORCID:0009000527154709), Livaudais, Ashia [Fermilab] (ORCID:000000033734335X), Nevin, Becky [Fermilab] (ORCID:0000000310568401), Paul, Omari [Fermilab] (ORCID:0009000587132077), Nord, Brian [Fermilab; Chicago U.; MIT, LNS] (ORCID:0000000167068972). 2025-02-11. DeepBench: A simulation package for physical benchmarking data. https://doi.org/10.21105/joss.06774
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