This is your work, valued
Earth observation Researcher at RISE. Previously at UoG, KTH, and UZH.
DS_UNet. [GSRL] Dual Stream U-Net architecture for urban change detection using Sentinel-1 and Sentinel-2 data fusion.
73ContUrbanCD. [TGRS] Continuous urban change detection from satellite image time series
39DDA_UrbanExtraction. [RSE] Unsupervised domain adaptation for global urban extraction using Sentinel-1 SAR and Sentinel-2 MSI data
30SiameseSSL. [IGRSS] Urban change detection with a Dual-Task Siamese network and semi-supervised learning
24DisasterAdaptiveNet. Python
14urban_change_detection. Python
11SemiSupervisedMultiModalCD. [RS] Semi-supervsed urban change detection with multi-modal Sentinel-1 SAR and Sentinel-2 MSI data.
10DDA_PopulationMapping. [JAG] Deep learning-based population mapping from Earth observation data in Sub-Saharan Africa
5multimodal_siamese_cd. Python
2PopulationGrowthMapping_Kigali. Population Growth Mapping in Kigali using bi-temporal Sentinel-2 data and a Siamese network trained with weak supervision at the census level
2gee_download. Python
1AG2413_project. Urban change detection for Sentinel-2 MSI imagery using a Siamese Network
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