"𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐃𝐚𝐭𝐚 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐟𝐨𝐫 𝐄𝐚𝐫𝐭𝐡 𝐎𝐛𝐬𝐞𝐫𝐯𝐚𝐭𝐢𝐨𝐧" 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩 𝐕𝐢𝐝𝐞𝐨𝐬 𝐑𝐞𝐥𝐞𝐚𝐬𝐞𝐝
We are thrilled to share that the videos from the "Machine Learning and Data Management for Earth Observation" workshop, held on March 18-19, 2024, are now accessible online. This event, meticulously organized by the Data Management and Machine Learning for Earth Observation Group and BIFOLD, featured 12 insightful sessions from esteemed experts who are pioneers in the field.
This workshop brought together leading researchers specializing in remote sensing, machine learning, signal and image processing, and big data management to discuss innovative approaches to handle and analyze this complex, heterogeneous data. The efficient processing and intelligent analysis of EO data are now essential for enhancing our understanding of the planet's current state and the changes it is undergoing, showcasing the critical role of data management and machine learning in driving forward the capabilities of artificial intelligence in Earth Observation.
Watch the sessions on our YouTube Playlist: https://lnkd.in/dXWtfEYr
Highlighted sessions include:
- Opening Remarks by Prof. Dr. Volker Markl and Prof. Dr. Begüm Demir
- Science in the Era of AI by Prof. Dr. Alex Szalay
- Unlocking the Potential of Planetary-Scale Machine Learning by Assist. Prof. Dr. Hannah Kerner
- Efficient Algorithms for Locally Private Learning by Dr. Vitaly Feldman
For a complete list of sessions and more information, visit our
workshop page: https://lnkd.in/dQzi_BXi
Special thanks to our distinguished partners: The Alan Turing Institute, Apple Research, Arizona State University, European Space Agency - ESA, German Aerospace Center (DLR), Humboldt-Universität zu Berlin, IBM Research, IEEE GRSM, The Johns Hopkins University, NASA - National Aeronautics and Space Administration, NASA Harvest, The Open Geospatial Consortium (OGC), SAR Technology, Sinergise, Technical University of Munich, The University of Bonn / Forschungszentrum Jülich, University of Pavia.
#EarthObservation #MachineLearning #DataManagement #BigData #EOData #SatelliteTechnology #AI #Geospatial #Research