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RaVÆn: unsupervised change detection of extreme events using ML on-board satellites
Applications such as disaster management enormously benefit from rapid availability of satellite observations. Traditionally, data analysis is performed on the ground after being transferred—downlinked—to a ground station. Constraints on the downlink capabilities, both in terms of data volume and ti...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9547912/ https://www.ncbi.nlm.nih.gov/pubmed/36209278 http://dx.doi.org/10.1038/s41598-022-19437-5 |