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Unsupervised Learning for Target Tracking and Background Subtraction in Satellite Imagery

Simulated data used to compare the performance of Jekyll and Hyde against a more traditional supervised Machine Learning approach.

Data and Resources

Cite this as

Jonathan S. Kenta, Charles C. Wamsley, Davin Flateau, Amber Fergusson (2024). Dataset: Unsupervised Learning for Target Tracking and Background Subtraction in Satellite Imagery. https://doi.org/10.57702/hvvezho5

DOI retrieved: December 16, 2024

Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.1117/12.2580620
Author Jonathan S. Kenta
More Authors
Charles C. Wamsley
Davin Flateau
Amber Fergusson