2 citations · 3 across the 6 of their papers we have counts for
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cs.LG2021
DOODLER: Determining Out-Of-Distribution Likelihood from Encoder Reconstructions
Jonathan S. Kent, Bo Li
Deep Learning models possess two key traits that, in combination, make their use in the real world a risky prospect. One, they do not typically generalize well outside of the distr…
cs.CV2021★ 2 cited
Unsupervised Learning for Target Tracking and Background Subtraction in Satellite Imagery
Jonathan S. Kent, Charles C. Wamsley, Davin Flateau +1
This paper describes an unsupervised machine learning methodology capable of target tracking and background suppression via a novel dual-model approach. ``Jekyll`` produces a video…