Award Data

To address the National Geospatial-Intelligence Agency (NGA) need for overhead imagery analysis algorithms that provide uncertaintymeasures for object recognition and aggregation, Intellisense Systems, Inc. (ISS) proposes to develop a new Variational Object Recognition andGrouping Network (VORGNet) system. It is based on the innovation of implementing a Bayesian convolutional neural network (CNN) ...

To address the Department of Homeland Security (DHS) need for a cell phone location finder for maritime and remote search and rescue (SAR), Physical Optics Corporation (POC) proposes to develop a new REmote Phone Locator for Improved Emergency Rescue (REPLIER). REPLIER leverages novel techniques recently developed at POC to extend the range of cellular communications and integrate commercial cellu ...

To address the DHS need to rapidly detect radio interference of critical radio frequency (RF) communications channels utilized by first responders, Physical Optics Corporation (POC) proposes to develop a new Miniature Intelligent Spectral Analyzer (MISCAN) device based on a combination of commercial off-the-shelf (COTS) electronic components in a custom software-defined configuration along with in ...

Toyon Research Corporation proposes to research and develop algorithms for low-shot object detection, adapting popular techniques to address the complexities inherent in ATR for remote sensing. Traditional object detection algorithms rely on large corpora of data which may not be available for more exotic targets (such as foreign military assets), and therefore, traditional Convolutional Neural Ne ...

The National Geospatial-Intelligence Agency (NGA) ingests and analyzes raw imagery from multiple sources to form actionable intelligenceproducts that can be disseminated across the intelligence community (IC). To effectively meet these demands NGA must continue to improveits automated and semi-automated methods for target detection and classification. Of particular concern is furthering NGA's abil ...

Building interpretable, composable autonomous systems requires consideration of uncertainties in the decisions and detections theygenerate. Human analysts need accurate absolute measures of probability to determine how to interpret and use the sometimes noisy resultsof machine learning systems; and composable autonomous systems need to be able to propagate uncertainties so that later reasoningsyst ...

On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

Toyon Research Corporation proposes to research and develop algorithms for generalized change detection, by leveraging and exploringexisting and proven effective traditional and deep learning methods, with a unique 3D reconstruction component. The vast majority of themassive amounts of imagery data will have small pixel level differences due to a multitude of unimportant changes: minor misregistra ...

We propose to build ARGON, the ARet Ground-to-Overhead Network. The network will ingest analyst-supplied ground-level imagery ofobjects and retrieve instances of those objects in overhead collections, providing tips back to the analysts. A proprietary method of trainingthe network, leveraging in-house capabilities, data sources, and tools, will be critical to its success. During Phase I, we will p ...

Drug overdose is now the leading cause of death for Americans under 50 years old, with fentanyl claiming more lives than any other drug.Alarmingly, the problem is increasing, with fentanyl overdoses claiming nearly twice as many lives in 2016 compared to 2015.In addition to users, first responders are at risk for coming into contact with fentanyl as they perform their duties.Fentanyl is extremely ...