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• Applying self-supervised learning for semantic cloud segmentation of all-sky images.

  Authors:Yann Fabel, Bijan Nouri, Stefan Wilbert, Niklas Blum, Rudolph Triebel, Marcel Hasenbalg, et al.From:Atmospheric Measurement Techniques (Vol. 15, Issue 3) Peer-Reviewed

  Feb. 14, 2022409 words Article Semantic segmentation of ground-based all-sky images (ASIs) can provide high-resolution cloud coverage information of distinct cloud types, applicable for meteorology-, climatology- and solar-energy-related applications....