activity
20142025
most citedAutomatic Detection of Solar Photovoltaic Arrays in High Resolution Aerial Imagery

198 citations · 324 across the 22 of their papers we have counts for

collaborators

22 papers

cs.LG2025

Ground tracking for improved landmine detection in a GPR system

Li Tang, Peter A. Torrione, Cihat Eldeniz +1

Ground penetrating radar (GPR) provides a promising technology for accurate subsurface object detection. In particular, it has shown promise for detecting landmines with low metal…

cs.CV2023★ 4 cited

Segment anything, from space?

Simiao Ren, Francesco Luzi, Saad Lahrichi +4

Recently, the first foundation model developed specifically for image segmentation tasks was developed, termed the "Segment Anything Model" (SAM). SAM can segment objects in input…

cs.CV2022★ 2 cited

Meta-Learning for Color-to-Infrared Cross-Modal Style Transfer

Evelyn A. Stump, Francesco Luzi, Leslie M. Collins +1

Recent object detection models for infrared (IR) imagery are based upon deep neural networks (DNNs) and require large amounts of labeled training imagery. However, publicly availab…

cs.LG2022★ 2 cited

Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling

Gregory P. Spell, Simiao Ren, Leslie M. Collins +1

We propose and show the efficacy of a new method to address generic inverse problems. Inverse modeling is the task whereby one seeks to determine the control parameters of a natura…

cs.CV2022

Transformers For Recognition In Overhead Imagery: A Reality Check

Francesco Luzi, Aneesh Gupta, Leslie Collins +2

There is evidence that transformers offer state-of-the-art recognition performance on tasks involving overhead imagery (e.g., satellite imagery). However, it is difficult to make u…

cs.CV2022

Meta-simulation for the Automated Design of Synthetic Overhead Imagery

Handi Yu, Simiao Ren, Leslie M. Collins +1

The use of synthetic (or simulated) data for training machine learning models has grown rapidly in recent years. Synthetic data can often be generated much faster and more cheaply…