SILO: A Machine Learning Dataset of Synthetic Ground-Based Observations of LEO Satellites
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/9161765/9172248/09172251.pdf?arnumber=9172251
Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. On-Earth Observation of Low Earth Orbit Targets through Phase Disturbances by Atmospheric Turbulence;Remote Sensing;2023-09-26
2. High-order pseudorange rate measurement model for multi-constellation LEO/INS integration: Case of Iridium-NEXT, Orbcomm, and Globalstar;Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering;2022-07-14
3. Stimulus: Accelerate Data Management for Scientific AI applications in HPC;2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid);2022-05
4. SpectraNet: Learned Recognition of Artificial Satellites from High Contrast Spectroscopic Imagery;2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2022-01
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