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Research PaperResearchia:202601.120a2556[Machine Learning > Machine Learning]

OceanSAR-2: A Universal Feature Extractor for SAR Ocean Observation

Alexandre Tuel

Abstract

We present OceanSAR-2, the second generation of our foundation model for SAR-based ocean observation. Building on our earlier release, which pioneered self-supervised learning on Sentinel-1 Wave Mode data, OceanSAR-2 relies on improved SSL training and dynamic data curation strategies, which enhances performance while reducing training cost. OceanSAR-2 demonstrates strong transfer performance across downstream tasks, including geophysical pattern classification, ocean surface wind vector and significant wave height estimation, and iceberg detection. We release standardized benchmark datasets, providing a foundation for systematic evaluation and advancement of SAR models for ocean applications.

Submission:1/12/2026
Comments:0 comments
Subjects:Machine Learning; Machine Learning
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OceanSAR-2: A Universal Feature Extractor for SAR Ocean Observation | Researchia