Abstract
The project aims to develop and apply innovative data analytic methods underpinned with machine (deep) learning technology to analyze and detect seismic anomalies from electromagnetic data observed by the SWARM and CSES satellites along with CSELF network.
| Original language | English |
|---|---|
| Number of pages | 2 |
| Publication status | Published (in print/issue) - 23 Jul 2021 |
| Event | The ESA-NRSCC Dragon 2021 Symposium - , Italy Duration: 19 Jul 2021 → 23 Jul 2021 https://dragon-symp2021.esa.int/ |
Conference
| Conference | The ESA-NRSCC Dragon 2021 Symposium |
|---|---|
| Country/Territory | Italy |
| Period | 19/07/21 → 23/07/21 |
| Internet address |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
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SDG 15 Life on Land
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