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gee_s1_ard
Creates an analysis ready sentinel-1 SAR image collection in Google Earth Engine by applying additional border noise correction, speckle filtering and radiometric terrain normalization.deSpeckNet-TF-GEE
This implementation uses python to seamlessly integrate Sentinel-1 SAR image preparation in GEE with deep learning in Tensorflow for SAR image despeckling.deSpeckNet
These are a set of scripts to train a deep learning based SAR image despeckling method.CV-deSpeckNet
This repo implements a complex-valued multi-stream fully convolutional network for PolSAR data despeckling.SAR-FCN-DK3
These are a set of functions to apply a fully convolutional network on a multi-temporal SAR images for semantic segmentation.S1-S2_Transformer
This implementation uses Google Earth Engine Python API to process Sentinel-1 SAR and Sentinel-2 optical timeseries for tropical dry forest disturbance mapping. It also uses Tensorflow to build a siamese transformer architecture to implicitly learn the seasonality in the two series to make a forest and non-forest inference.Love Open Source and this site? Check out how you can help us