3 citations · 5 across the 9 of their papers we have counts for
10 papers
From Pixels to Planes: Minimum Ground Sample Distance for Aircraft
Matthew Ciolino, Willie Maddox
This study investigates the impact of ground sample distance (GSD) on the detection performance of various sized aircraft using the proprietary AllPlanes 120 dataset. The data set…
Image Compression and Actionable Intelligence With Deep Neural Networks
Matthew Ciolino
If a unit cannot receive intelligence from a source due to external factors, we consider them disadvantaged users. We categorize this as a preoccupied unit working on a low connect…
Enhancing Satellite Imagery using Deep Learning for the Sensor To Shooter Timeline
Matthew Ciolino, Dominick Hambrick, David Noever
The sensor to shooter timeline is affected by two main variables: satellite positioning and asset positioning. Speeding up satellite positioning by adding more sensors or by decrea…
Color Teams for Machine Learning Development
Josh Kalin, David Noever, Matthew Ciolino
Machine learning and software development share processes and methodologies for reliably delivering products to customers. This work proposes the use of a new teaming construct for…
Automating Defense Against Adversarial Attacks: Discovery of Vulnerabilities and Application of Multi-INT Imagery to Protect Deployed Models
Josh Kalin, David Noever, Matthew Ciolino +2
Image classification is a common step in image recognition for machine learning in overhead applications. When applying popular model architectures like MobileNetV2, known vulnerab…
A Modified Drake Equation for Assessing Adversarial Risk to Machine Learning Models
Josh Kalin, David Noever, Matthew Ciolino
Machine learning models present a risk of adversarial attack when deployed in production. Quantifying the contributing factors and uncertainties using empirical measures could assi…
Fortify Machine Learning Production Systems: Detect and Classify Adversarial Attacks
Matthew Ciolino, Josh Kalin, David Noever
Production machine learning systems are consistently under attack by adversarial actors. Various deep learning models must be capable of accurately detecting fake or adversarial in…
Black Box to White Box: Discover Model Characteristics Based on Strategic Probing
Josh Kalin, Matthew Ciolino, David Noever +1
In Machine Learning, White Box Adversarial Attacks rely on knowing underlying knowledge about the model attributes. This works focuses on discovering to distrinct pieces of model i…
The Go Transformer: Natural Language Modeling for Game Play
Matthew Ciolino, David Noever, Josh Kalin
This work applies natural language modeling to generate plausible strategic moves in the ancient game of Go. We train the Generative Pretrained Transformer (GPT-2) to mimic the sty…
Discoverability in Satellite Imagery: A Good Sentence is Worth a Thousand Pictures
David Noever, Wes Regian, Matt Ciolino +3
Small satellite constellations provide daily global coverage of the earth's landmass, but image enrichment relies on automating key tasks like change detection or feature searches.…