A Radar Echo Simulator for the Synthesis of Randomized Training Data Sets in the Context of AI-Based Applications
Jonas Schorlemer,
Jochen Altholz,
Jan Barowski
et al.
Abstract:Supervised machine learning algorithms usually require huge labeled data sets to produce sufficiently good results. For many applications, these data sets are still not available today, and the reasons for this can be manifold. As a solution, the missing training data can be generated by fast simulators. This procedure is well studied and allows filling possible gaps in the training data, which can further improve the results of a machine learning model. For this reason, this article deals with the development… Show more
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