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A deep network approach to multitemporal cloud detection

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arxiv 2012.10393 v1 pith:36QPSCEV submitted 2020-12-09 physics.ao-ph cs.LG

Devis Tuia , Benjamin Kellenberger , Adrian Pérez-Suay , Gustau Camps-Valls This is my paper
classification physics.ao-phcs.LG
keywords modelcloudcloudsdeepnetworktimeableaccuracy
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We present a deep learning model with temporal memory to detect clouds in image time series acquired by the Seviri imager mounted on the Meteosat Second Generation (MSG) satellite. The model provides pixel-level cloud maps with related confidence and propagates information in time via a recurrent neural network structure. With a single model, we are able to outline clouds along all year and during day and night with high accuracy.

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