1 citations · 2 across the 3 of their papers we have counts for
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Deep Learning Framework for Detecting Ground Deformation in the Built Environment using Satellite InSAR data
Nantheera Anantrasirichai, Juliet Biggs, Krisztina Kelevitz +5
The large volumes of Sentinel-1 data produced over Europe are being used to develop pan-national ground motion services. However, simple analysis techniques like thresholding canno…
A deep learning approach to detecting volcano deformation from satellite imagery using synthetic datasets
Nantheera Anantrasirichai, Juliet Biggs, Fabien Albino +1
Satellites enable widespread, regional or global surveillance of volcanoes and can provide the first indication of volcanic unrest or eruption. Here we consider Interferometric Syn…
Detecting Volcano Deformation in InSAR using Deep learning
N. Anantrasirichai, F. Albino, P. Hill +2
Globally 800 million people live within 100 km of a volcano and currently 1500 volcanoes are considered active, but half of these have no ground-based monitoring. Alternatively, sa…