4 papers
Combining Sentinel-1 and Sentinel-2 Time Series via RNN for object-based land cover classification
Dino Ienco, Raffaele Gaetano, Roberto Interdonato +2
Radar and Optical Satellite Image Time Series (SITS) are sources of information that are commonly employed to monitor earth surfaces for tasks related to ecology, agriculture, mobi…
DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn
Roberto Interdonato, Dino Ienco, Raffaele Gaetano +1
Nowadays, modern Earth Observation systems continuously generate huge amounts of data. A notable example is represented by the Sentinel-2 mission, which provides images at high spa…
MRFusion: A Deep Learning architecture to fuse PAN and MS imagery for land cover mapping
Raffaele Gaetano, Dino Ienco, Kenji Ose +1
Nowadays, Earth Observation systems provide a multitude of heterogeneous remote sensing data. How to manage such richness leveraging its complementarity is a crucial chal- lenge in…
M3Fusion: A Deep Learning Architecture for Multi-{Scale/Modal/Temporal} satellite data fusion
P. Benedetti, D. Ienco, R. Gaetano +3
Modern Earth Observation systems provide sensing data at different temporal and spatial resolutions. Among optical sensors, today the Sentinel-2 program supplies high-resolution te…