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@@ -115,7 +115,7 @@ Version 1.0 of the dataset that contains data across Africa, (20% of the global
 41 orthophotos (9000x9000 px) over Poland, Aerial Imagery (25cm & 50cm res.), manual segmentations masks for Buildings, Woodland and Water, Paper: [Boguszewski et al., 2020](https://arxiv.org/abs/2005.02264)
 
 - [**95-Cloud: A Cloud Segmentation Dataset**](https://github.com/SorourMo/95-Cloud-An-Extension-to-38-Cloud-Dataset) *(S. Mohajerani et. all, Jan 2020)*  
-34701 manually segmented 384x384 patches with cloud masks, Landsat 8 imagery (R,G,B,NIR; 30 m res.), Paper: [Mohajerani et al. 2019](https://arxiv.org/abs/2001.08768)
+34701 manually segmented 384x384 patches with cloud masks, Landsat 8 imagery (R,G,B,NIR; 30 m res.), Paper: [Mohajerani et al. 2021](https://ieeexplore.ieee.org/document/9394710)
 
 - [**Open Cities AI Challenge**](https://www.drivendata.org/competitions/60/building-segmentation-disaster-resilience/page/150/) *(GFDRR, Mar 2020)* .   
 790k building footprints from Openstreetmap (2 label quality categories), aerial imagery (0.03-0.2m resolution, RGB, 11k 1024x1024 chips, COG format), 10 cities in Africa.