11 citations · 11 across the 4 of their papers we have counts for
5 papers
Evaluating Graph Neural Networks for Change-Criticality Classification in Maritime Navigation Charts
Abhishek Potnis, Jacob Arndt
Graph neural networks (GNNs) are a class of neural networks suitable for learning on graph-structured data. Their application to spatial data is a natural extension, however its re…
Electronic Navigational Chart Change Classification
Jacob Arndt, Abhishek Potnis, Alexandre Sorokine
Electronic Navigational Charts (ENCs) are geospatial vector datasets used in maritime navigation systems that represent hydrographic and navigational information such as depths, na…
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…
SimLBR: Learning to Detect Fake Images by Learning to Detect Real Images
Aayush Dhakal, Subash Khanal, Srikumar Sastry +4
The rapid advancement of generative models has made the detection of AI-generated images a critical challenge for both research and society. Recent works have shown that most state…
OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery
Philipe Dias, Aristeidis Tsaris, Jordan Bowman +4
While the pretraining of Foundation Models (FMs) for remote sensing (RS) imagery is on the rise, models remain restricted to a few hundred million parameters. Scaling models to bil…