5 papers
Emerging Flexible Designs for Geospatial Multimodal Foundation Models
Philipe Dias, Waqwoya Abebe, Abhishek Potnis +4
Foundation models are rapidly transforming Earth observation by enabling scalable pretraining across diverse unlabeled geospatial modalities. However, their architectural diversity…
FOCUS: Fused Observation of Channels for Unveiling Spectra
Xi Xiao, Aristeidis Tsaris, Anika Tabassum +4
Hyperspectral imaging (HSI) captures hundreds of narrow, contiguous wavelength bands, making it a powerful tool in biology, agriculture, and environmental monitoring. However, inte…
ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling
Xiao Wang, Jong-Youl Choi, Takuya Kurihaya +15
Sparse observations and coarse-resolution climate models limit effective regional decision-making, underscoring the need for robust downscaling. However, existing AI methods strugg…
Distributed Cross-Channel Hierarchical Aggregation for Foundation Models
Aristeidis Tsaris, Isaac Lyngaas, John Lagregren +6
Vision-based scientific foundation models hold significant promise for advancing scientific discovery and innovation. This potential stems from their ability to aggregate images fr…
OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery
Philipe Dias, Aristeidis Tsaris, Jordan Bowman +4
While the pretraining of Foundation Models (FMs) for remote sensing (RS) imagery is on the rise, models remain restricted to a few hundred million parameters. Scaling models to bil…