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Cloud Removal

The majority of all optical observations collected via spaceborne satellites are affected by haze or clouds. Consequently, persistent cloud coverage affects the remote sensing practitioner's capabilities of a continuous and seamless monitoring of our planet. Cloud removal is the task of reconstructing cloud-covered information while preserving originally cloud-free details.

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Papers

Showing 3140 of 56 papers

TitleStatusHype
Cloud removal Using Atmosphere Model0
GLF-CR: SAR-Enhanced Cloud Removal with Global-Local FusionCode1
Attention mechanism-based generative adversarial networks for cloud removal in Landsat images0
Enhancing Satellite Imagery using Deep Learning for the Sensor To Shooter Timeline0
SEN12MS-CR-TS: A Remote Sensing Data Set for Multi-modal Multi-temporal Cloud RemovalCode1
Cloud Removal from Satellite Images0
SSSNET: Semi-Supervised Signed Network ClusteringCode1
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention NetworksCode1
Spatio-Temporal SAR-Optical Data Fusion for Cloud Removal via a Deep Hierarchical ModelCode1
Seeing Through Clouds in Satellite ImagesCode1
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