Award Data

To address the NGA’s need to fully automate recovery of camera orientation parameters from ground-level imagery, Physical Optics Corporation (POC) proposes to develop new Automated Camera Orientation Recovery Software (ACORS). It is based on a new, multicue combination of algorithms for finding true horizon lines in images. Specifically, the innovation in locating occluded true horizon lines bel ...

Due to the lack of consistency in existing automated methods for assigning VNIIRS levels to motion imagery, and the overwhelming human resources required to manually assign levels, a new method of automated/semi-automated VNIIRS assessment is needed. In recent years, advancements in deep learning have provided solutions to previously intractable computer vision problems. In many cases, automated d ...

To address NGA’s requirements, Sonalysts’ team of world-class experts in underwater optical communication proposes development and implementation of the Precision Optical Navigation Transceiver for Undersea Systems (PONTUS). PONTUS will transfer navigation information from an Underwater Navigation Beacon (UNB) to an Unmanned Undersea Vehicle (UUV) in an electromagnetic-spectrum-denied (e.g., G ...

SA Photonics’ Optical Navigation and Ranging (ONAR) system is an interrogative system that operate underwater in wavelength range of blue/green (450-540 nm) and enables navigational correction to IMU based dead reckoning navigation. The location based beacons are battery operated and have operational life span of over one year. The system is designed to operate in on demand burst mode so that no ...

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 ...

Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

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) ...

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 ...

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 ...

To address the NGA need for algorithms that fuse observables from over-flight operations and from ground sources to automatically estimatethe degradation of urban environments due to battle damage or natural disasters, Intellisense Systems, Inc. (ISS) proposes to develop a newBayesian Urban Degradation Assessment (BUDA) software system. It is based on the integration of multiple damage assessment ...