SEMANTIC SEGMENTATION USING A UNET ARCHITECTURE ON SENTINEL-2 DATA

5 citations as recorded by crossref.

1. Enhancing Autonomous Visual Perception in Challenging Environments: Bilateral Models with Vision Transformer and Multilayer Perceptron for Traversable Area Detection C. Urrea & M. Vélez https://doi.org/10.3390/technologies12100201
2. Empirical Evaluation of UNet for Segmentation of Applicable Surfaces for Seismic Sensor Installation M. Uzdiaev et al. https://doi.org/10.3390/jimaging12010034
3. SEMANTIC SEGMENTATION OF ALGAL BLOOMS ON THE OCEAN SURFACE USING SENTINEL 3 CHL_NN BAND IMAGERY V. BHANDAGE & M. PAI M. M. https://doi.org/10.35784/acs-2024-27
4. Deep learning applications on satellite imagery datasets for nuclear nonproliferation and counter-proliferation J. Han et al. https://doi.org/10.1016/j.anucene.2025.111443
5. Use of the SNOWED Dataset for Sentinel-2 Remote Sensing of Water Bodies: The Case of the Po River M. Scarpetta et al. https://doi.org/10.3390/s24175827