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Machine Learning based Uncertainty Quantification for Wind- Tracking Algorithms

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dc.contributor.author Teixeira, Joaquim
dc.contributor.author Nguyen, Hai
dc.contributor.author Posselt, Derek
dc.contributor.author Su, Hui
dc.date.accessioned 2021-03-29T23:20:10Z
dc.date.available 2021-03-29T23:20:10Z
dc.date.issued 2019-08-11
dc.identifier.citation SPIE Optics and Photonics 2019, San Diego, California, August 11-15, 2019 en_US
dc.identifier.clearanceno 19-5143
dc.identifier.uri http://hdl.handle.net/2014/51634
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en_US en_US
dc.publisher Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2019 en_US
dc.title Machine Learning based Uncertainty Quantification for Wind- Tracking Algorithms en_US
dc.type Presentation en_US


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