OmniCloudMask is a Python library for fast, accurate cloud and cloud shadow segmentation in satellite imagery.
CloudGAN: Detecting and removing clouds from satellite RGB-images
To process a Sentinel-2 time series with MAJA cloud detection and atmospheric correction processor
To download products provided by Theia land data center : https://theia.cnes.fr
Understanding the Role of Receptive Field of Convolutional Neural Network for Cloud Detection in Landsat 8 OLI Imagery
CD-Mamba: Cloud Detection with Long-Range Spatial Dependency Modeling
Weak-to-Strong Consistency Learning for Semi-Supervised Cloud Detection
Detected cloud in publically available satellite imagery from Sentinal 2 mission. Team project for the CloudNCloud competition hosted by Microsoft AI at DrivenData.
Cloud Detection Model for Sentinel-2 Imagery (see https://registry.opendata.aws/sentinel-2/)
Public code for "Precise Forecasting of Sky Images Using Spatial Warping", ICCVW 2021
A follow up demo of my work done for the on-cloud-n competition
Cloud Detection on Satellites Using Deep Learning
Sky Quality Meter (SQM) and Cloud Detection sensor for astronomical observatories
Repository for the code of my Bachelor's thesis
A small python package for fast and scalable detection, removal and/or filling of anomalous pixels in satellite images.
The definitive Python implementation of FMask 4.3 for Landsat 8 and Sentinel 2
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