ViT-Large with focal loss on Sentinel-1 SAR data reaches 69.6% held-out accuracy and 83.9% precision on minority multi-year ice, establishing a data-centric baseline for sea ice classification.
Advancing arctic sea ice remote sensing with ai and deep learning: Opportunities and challenges
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A Data-Centric Vision Transformer Baseline for SAR Sea Ice Classification
ViT-Large with focal loss on Sentinel-1 SAR data reaches 69.6% held-out accuracy and 83.9% precision on minority multi-year ice, establishing a data-centric baseline for sea ice classification.