5 papers
A Comparison of Data Augmentation Methods for Training Deep Neural Networks on Synthetic Aperture Sonar
C. J. Moore, Gregory D. Vetaw, Jordan Malof
In this work we study Automatic Target Recognition (ATR) for Synthetic Aperture Sonar (SAS) data with a focus on deep neural networks (DNNs). The main challenge in training DNNs fo…
Global Building Area Estimation Products: How Accurate Are They?
Saad Lahrichi, Doa'a Allabadi, Kyle Bradbury +1
Geo-spatial rasters of building footprint area are useful for a variety of tasks, such as monitoring urbanization, improving energy efficiency, and tracking greenhouse gas emission…
Closing Gaps in Emissions Monitoring with Climate TRACE
Brittany V. Lancellotti, Jordan M. Malof, Aaron Davitt +32
Global greenhouse gas emissions estimates are essential for monitoring and mitigation planning. Existing emissions datasets provide critical foundations for understanding emissions…
Improving and Evaluating Open Deep Research Agents
Doaa Allabadi, Kyle Bradbury, Jordan M. Malof
We focus here on Deep Research Agents (DRAs), which are systems that can take a natural language prompt from a user, and then autonomously search for, and utilize, internet-based c…
Is Self-Supervised Pre-training on Satellite Imagery Better than ImageNet? A Systematic Study with Sentinel-2
Saad Lahrichi, Zion Sheng, Shufan Xia +2
Self-supervised learning (SSL) has demonstrated significant potential in pre-training robust models with limited labeled data, making it particularly valuable for remote sensing (R…