A deep network approach to multitemporal cloud detection

Autor:	Tuia, Devis, Kellenberger, Benjamin, Pérez-Suay, Adrian, Camps-Valls, Gustau
Rok vydání:	2020
Předmět:	Physics - Atmospheric and Oceanic Physics Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	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.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2012.10393 Zobrazit plný text záznamu View this record from Arxiv