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A critical review on the state-of-the-art and future prospects of Machine Learning for Earth Observation Operations
Abstract The continuing Machine Learning (ML) revolution indubitably has had a significant
positive impact on the analysis of downlinked satellite data. Other aspects of the Earth …
positive impact on the analysis of downlinked satellite data. Other aspects of the Earth …
Reinforcement learning for the agile earth-observing satellite scheduling problem
This work explores reinforcement learning (RL) for on-board planning and scheduling of an
agile Earth-observing satellite (AEOS). In this formulation of the AEOS scheduling problem …
agile Earth-observing satellite (AEOS). In this formulation of the AEOS scheduling problem …
Reinforcement Learning for Spacecraft Planning and Scheduling
AP Herrmann - 2023 - search.proquest.com
The coming decades of space exploration will require a massive increase in spacecraft
autonomy due to an explosion in the number of Earth-orbiting satellites, which will tax …
autonomy due to an explosion in the number of Earth-orbiting satellites, which will tax …
[PDF][PDF] Machine Learning in Earth Observation Operations: A review Pablo Miralles, Antonio Fulvio Scannapieco, Nitya Jagadam, Prerna Baranwal, Bhavin Faldu …
Z Di Fraia, D Wischert, D Stepanova - 2021 - researchgate.net
Abstract Analysis of downlinked satellite imagery has undeniably benefited greatly from the
ongoing Machine Learning (ML) revolution. Other aspects of the Earth Observation industry …
ongoing Machine Learning (ML) revolution. Other aspects of the Earth Observation industry …