18 citations · 30 across the 5 of their papers we have counts for
9 papers
Sparse InSAR Data 3D Inpainting for Ground Deformation Detection Along the Rail Corridor
Odysseas Pappas, Juliet Biggs, David Bull +2
Monitoring of ground movement close to the rail corridor, such as that associated with landslips caused by ground subsidence and/or uplift, is of great interest for the detection a…
Analysis of Vision-based Abnormal Red Blood Cell Classification
Annika Wong, Nantheera Anantrasirichai, Thanarat H. Chalidabhongse +3
Identification of abnormalities in red blood cells (RBC) is key to diagnosing a range of medical conditions from anaemia to liver disease. Currently this is done manually, a time-c…
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…
Fast Depth Estimation for View Synthesis
Nantheera Anantrasirichai, Majid Geravand, David Braendler +1
Disparity/depth estimation from sequences of stereo images is an important element in 3D vision. Owing to occlusions, imperfect settings and homogeneous luminance, accurate estimat…
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…