Pretraining Billion-scale Geospatial Foundational Models on Frontier

As AI workloads increase in scope, generalization capability becomes challenging for small task-specific models and their demand for large amounts of labeled training samples increases. On the contrary, Foundation Models (FMs) are trained with internet-scale unlabeled data via self-supervised learni...

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Hauptverfasser:	Tsaris, Aristeidis, Dias, Philipe Ambrozio, Potnis, Abhishek, Yin, Junqi, Wang, Feiyi, Lunga, Dalton
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence
Online-Zugang:	Volltext bestellen
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