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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 2130 of 56 papers

TitleStatusHype
SSSNET: Semi-Supervised Signed Network ClusteringCode1
Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusionCode1
GLF-CR: SAR-Enhanced Cloud Removal with Global-Local FusionCode1
Attentive Contextual Attention for Cloud RemovalCode1
Multi-Head Linear Attention Generative Adversarial Network for Thin Cloud Removal0
Attention mechanism-based generative adversarial networks for cloud removal in Landsat images0
Cloud Removal from Satellite Images0
Cloud Removal in Remote Sensing Using Sequential-Based Diffusion Models0
Cloud removal Using Atmosphere Model0
Cloud Removal with Fusion of High Resolution Optical and SAR Images Using Generative Adversarial Networks0
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