16 citations · 17 across the 2 of their papers we have counts for
3 papers
Fine-tuning of Geospatial Foundation Models for Aboveground Biomass Estimation
Michal Muszynski, Levente Klein, Ademir Ferreira da Silva +13
Global vegetation structure mapping is critical for understanding the global carbon cycle and maximizing the efficacy of nature-based carbon sequestration initiatives. Moreover, ve…
Foundation Models for Generalist Geospatial Artificial Intelligence
Johannes Jakubik, Sujit Roy, C. E. Phillips +30
Significant progress in the development of highly adaptable and reusable Artificial Intelligence (AI) models is expected to have a significant impact on Earth science and remote se…
TensorBank: Tensor Lakehouse for Foundation Model Training
Romeo Kienzler, Leonardo Pondian Tizzei, Benedikt Blumenstiel +9
Storing and streaming high dimensional data for foundation model training became a critical requirement with the rise of foundation models beyond natural language. In this paper we…