87 citations · 142 across the 12 of their papers we have counts for
4 papers · 1 filter
Atmospheric turbulence removal using convolutional neural network
Jing Gao, N. Anantrasirichai, David Bull
This paper describes a novel deep learning-based method for mitigating the effects of atmospheric distortion. We have built an end-to-end supervised convolutional neural network (C…
HABNet: Machine Learning, Remote Sensing Based Detection and Prediction of Harmful Algal Blooms
P. R. Hill, A. Kumar, M. Temimi +1
This paper describes the application of machine learning techniques to develop a state-of-the-art detection and prediction system for spatiotemporal events found within remote sens…
The application of Convolutional Neural Networks to Detect Slow, Sustained Deformation in InSAR Timeseries
N. Anantrasirichai, J. Biggs, F. Albino +1
Automated systems for detecting deformation in satellite InSAR imagery could be used to develop a global monitoring system for volcanic and urban environments. Here we explore the…
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…