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Multi-temporal data augmentation for high frequency satellite imagery: a case study in Sentinel-1 and Sentinel-2 building and road segmentation
(ISPRS, 2022)
Contribución a congreso / Biltzarrerako ekarpena,
Semantic segmentation of remote sensing images has many practical applications such as urban planning or disaster assessment.
Deep learning-based approaches have shown their usefulness in automatically segmenting large ...
Super-resolution for Sentinel-2 images
(International Society for Photogrammetry and Remote Sensing, 2019)
info:eu-repo/semantics/conferenceObject,
Obtaining Sentinel-2 imagery of higher spatial resolution than the native bands while ensuring that output imagery preserves the original radiometry has become a key issue since the deployment of Sentinel-2 satellites. ...
Learning super-resolution for Sentinel-2 images with real ground truth data from a reference satellite
(Copernicus, 2020)
info:eu-repo/semantics/conferenceObject,
Copernicus program via its Sentinel missions is making earth observation more accessible and affordable for everybody. Sentinel-2 images provide multi-spectral information every 5 days for each location. However, the maximum ...