39 citations · 63 across the 5 of their papers we have counts for
5 papers
Regression Networks For Calculating Englacial Layer Thickness
Debvrat Varshney, Maryam Rahnemoonfar, Masoud Yari +1
Ice thickness estimation is an important aspect of ice sheet studies. In this work, we use convolutional neural networks with multiple output nodes to regress and learn the thickne…
Deep Tiered Image Segmentation For Detecting Internal Ice Layers in Radar Imagery
Yuchen Wang, Mingze Xu, John Paden +3
Understanding the structure of Earth's polar ice sheets is important for modeling how global warming will impact polar ice and, in turn, the Earth's climate. Ground-penetrating rad…
Deep Ice Layer Tracking and Thickness Estimation using Fully Convolutional Networks
Debvrat Varshney, Maryam Rahnemoonfar, Masoud Yari +1
Global warming is rapidly reducing glaciers and ice sheets across the world. Real time assessment of this reduction is required so as to monitor its global climatic impact. In this…
Multi-Task Spatiotemporal Neural Networks for Structured Surface Reconstruction
Mingze Xu, Chenyou Fan, John D Paden +2
Deep learning methods have surpassed the performance of traditional techniques on a wide range of problems in computer vision, but nearly all of this work has studied consumer phot…
Automatic Estimation of Ice Bottom Surfaces from Radar Imagery
Mingze Xu, David J Crandall, Geoffrey C Fox +1
Ground-penetrating radar on planes and satellites now makes it practical to collect 3D observations of the subsurface structure of the polar ice sheets, providing crucial data for…