39 citations · 59 across the 6 of their papers we have counts for
6 papers
AI-ready Snow Radar Echogram Dataset (SRED) for climate change monitoring
Oluwanisola Ibikunle, Hara Talasila, Debvrat Varshney +3
Tracking internal layers in radar echograms with high accuracy is essential for understanding ice sheet dynamics and quantifying the impact of accelerated ice discharge in Greenlan…
Hierarchical Information-sharing Convolutional Neural Network for the Prediction of Arctic Sea Ice Concentration and Velocity
Younghyun Koo, Maryam Rahnemoonfar
Forecasting sea ice concentration (SIC) and sea ice velocity (SIV) in the Arctic Ocean is of great significance as the Arctic environment has been changed by the recent warming cli…
Skip-WaveNet: A Wavelet based Multi-scale Architecture to Trace Snow Layers in Radar Echograms
Debvrat Varshney, Masoud Yari, Oluwanisola Ibikunle +4
Airborne radar sensors capture the profile of snow layers present on top of an ice sheet. Accurate tracking of these layers is essential to calculate their thicknesses, which are r…
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…
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding
Maryam Rahnemoonfar, Tashnim Chowdhury, Argho Sarkar +3
Visual scene understanding is the core task in making any crucial decision in any computer vision system. Although popular computer vision datasets like Cityscapes, MS-COCO, PASCAL…
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…