A self-supervised learning based approach to analyze Martian water–ice cloud properties for planetary atmospheric applications-Reference-Cited by-同舟云学术

A self-supervised learning based approach to analyze Martian water–ice cloud properties for planetary atmospheric applications

Published:2021-04 Issue: Volume:181 Page:1-13
ISSN:0094-5765
Container-title:Acta Astronautica
language:en
Short-container-title:Acta Astronautica

Author:

Campbell Charissa L.^ORCID,Meka Shiv,Marrable Daniel,Rohl Andrew L.^ORCID,Chai Kevin^ORCID,Benedix Gretchen K.,Smith Christina L.,Moores John E.^ORCID

Publisher

Elsevier BV

Subject

Aerospace Engineering

Reference23 articles.

1. Estimating the altitudes of martian water-ice clouds above the mars science laboratory rover landing site;Campbell;Planet. Space Sci.,2020

2. Constraints on mars aphelion cloud belt phase function and ice crystal geometries;Cooper;Planet. Space Sci.,2019

3. Observations of wind direction by automated analysis of images from mars and the MSL rover;Francis;Acta Astronaut.,2014

4. The first martian year of cloud activity from mars science laboratory (sol 0-800);Kloos;Adv. Space Res.,2016

5. Interannual and diurnal variability in water ice clouds observed from MSL over two martian years;Kloos;J. Geophys. Res. (Planets),2018

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1. Five Mars Years of Cloud Observations at Gale Crater: Opacities, Variability, and Ice Crystal Habits;The Planetary Science Journal;2024-02-01

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