Abstract
Hyperspectral imaging has become a mature technology which brings exciting possibilities in various Earth observation applications in a plethora of fields, including precision agriculture, forestry, event detection and tracking, and more. However, high dimensionality is an important obstacle in its effective transfer from a satellite back to Earth for further processing. To tackle it and enable faster adoption of the hyperspectral technology in practice, the on-board data processing has become critical, as it allows to substantially reduce the data dimensionality before transferring it, and to extract value from raw data. In this paper, we present Leopard - a CubeSat standard compliant Data Processing Unit (DPU) which enables mission designers to apply Artificial Intelligence solutions in space.
| Original language | English |
|---|---|
| Journal | Proceedings of the International Astronautical Congress, IAC |
| Volume | 2020-October |
| Publication status | Published - 2020 |
| Event | 71st International Astronautical Congress, IAC 2020 - Virtual, Online Duration: 12 Oct 2020 → 14 Oct 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger
Keywords
- DPU
- Deep learning
- FPGA
- Hyperspectral imaging
- On-board processing
ASJC Scopus subject areas
- Aerospace Engineering
- Astronomy and Astrophysics
- Space and Planetary Science
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