39 citations · 50 across the 9 of their papers we have counts for
9 papers
Towards a satellite image manipulation and deepfake localization benchmark dataset
Jacob Arndt, Debvrat Varshney, Philipe Dias +1
Verifying the authenticity of satellite imagery has become increasingly critical given advances in generative artificial intelligence. Highly realistic synthetic imagery produced f…
Geospatial Diffusion for Land Cover Imperviousness Change Forecasting
Debvrat Varshney, Vibhas Vats, Bhartendu Pandey +2
Land cover, both present and future, has a significant effect on several important Earth system processes. For example, impervious surfaces heat up and speed up surface water runof…
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…
A Global Analysis of Pre-Earthquake Ionospheric Anomalies
Luke Cullen, Andy W Smith, Asadullah H Galib +5
Local ionospheric density anomalies have been reported in the days prior to major earthquakes. This global study statistically investigates whether consistent ionospheric anomalies…
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…
Multiresolution Fully Convolutional Networks to detect Clouds and Snow through Optical Satellite Images
Debvrat Varshney, Claudio Persello, Prasun Kumar Gupta +1
Clouds and snow have similar spectral features in the visible and near-infrared (VNIR) range and are thus difficult to distinguish from each other in high resolution VNIR images. W…
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…