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On-Board Decision Making in Space with Deep Neural Networks and RISC-V Vector Processors
2021
Journal of Aerospace Information Systems
The use of deep neural networks (DNNs) in terrestrial applications went from niche to widespread in a few years, thanks to relatively inexpensive hardware for both training and inference, and large datasets available. The applicability of this paradigm to space systems, where both large datasets and inexpensive hardware are not readily available, is more difficult and thus still rare. This paper analyzes the impact of DNNs on the system-level capabilities of space systems in terms of on-board
doi:10.2514/1.i010916
fatcat:u4kjrzl7ozaihoswvdsbn2ezoa