ListarTFM: Màster Universitari Erasmus Mundus en Tecnologia Geoespacial por tema "deep learning"
Mostrando ítems 1-4 de 4
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Deep learning for studying urban water bodies' spatio-temporal transformation: a study of Chittagong City, Bangladesh
Universitat Jaume I (2021-03-05)Water has been playing a key role in human life since the dawn of civilization. It is an integral part of our lives. In recent years, water bodies specially, urban water bodies are in a poor state due to climate change and ... -
Enhancing temporal series of Sentinel-2 and Sentinel-3 data products: from classical regression to deep learning approach
Universitat Jaume I (2021-03-05)The free and open availability of satellite images covering global extent in recent days provides many novel opportunities for global monitoring of the earth’s surface. Sentinel-2 (S2) and Sentinel-3 (S3) satellite missions ... -
Extracting surface water bodies from Sentinel-2 imaginery using convolutional neural networks
Universitat Jaume I (2021-03-05)Water is an integral part of eco-system with significant role in human life. It is immensely mobilized natural resource and hence it should be monitored continuously. Water features extracted from satellite images can be ... -
Informal settlement segmentation using VHR RGB and height information from UAV Imagery: a case study of Nepal
Universitat Jaume I (2021-03-05)Informal settlement in developing countries are complex. They are contextually and radiometrically very similar to formal settlement. Resolution offered by Remote sensing is not sufficient to capture high variations and ...