Award Data

Newer techniques in data collection such as Lidar and photogrammetry can provide large quantities of accurate and up-to-date source data models in operational areas, but transforming this often massive amount of raw source data into a lightweight 3D representation that can be quickly consumed by defense customers using a web browser or mobile devices remains a challenging problem. While point clou ...

US military and intelligence agencies have invested significant resources in data collection and effective search and analytics tools. However, due to increasing amounts of data, finding relevant information has become more difficult. Thus, there is an important need for recommender system technology that pushes relevant un-queried data to analysts through automation and machine learning technique ...

NLP pipelines available today are getting robust for general language modeling purposes. But domain-specific data, abbreviations and lingos, and text about time or space still need a lot of tuning and training that are well beyond application of standard tool sets. Deep learning for recommendation engines is quite new, and all recommender systems, in particular for specially trained users, tend to ...

Advances in location-acquisition and mobile computing techniques have generated massive spatiotemporal trajectory data, which represent the mobility of a diversity of moving objects, such as people, vehicles, and animals. Moreover, recent research has tabbed learning of how to automatically explain and anticipate both the observable and abstract trajectories as one of the likely keys to building t ...

Recent advances in LiDAR, detector, and airborne systems technology have opened the door to small, high-performance, and significantly lower-cost alternatives over currently deployed airborne LiDAR imaging systems. CSLabs’ proposed initiative leverages modeling and simulation (M&S) to evaluate the efficacy of new approaches with the potential to disrupt the existing LiDAR imaging paradigm. Where ...

Traditional active 3D imaging systems, such as airborne and terrestrial lidar scanners, use a transmitter and receiver typically co-located on the same platform and connected in synchronous communications. However, recent advances in laser, detector, and airborne systems technology have opened the door to smaller, higher-performance and significantly lower-cost airborne lidar systems in which it i ...

The Video National Imagery Interpretability Rating Scale (VNIIRS) defines different levels of interpretability based on the types of tasks an analyst can perform with videos of a given VNIIRS rating. DoD users of motion imagery rely on NGA to rate the interpretability of motion image clips and understand the factors affecting the VNIIRS of operational imagery. To develop and validate and verify an ...

Intelligent Automation Inc. (IAI), along with our collaborators propose to develop a video tagging and statistics toolkit called VAST-CQA (Video Annotation and Statistics Toolkit for Crowdsourcing Quality Assessment). The key idea of the proposed approach is to provide a video quality annotation toolkit which reduces the effects of bias, subjective assessment and other human factors using a set of ...

Video analysts have to sift through voluminous video data to extract information of interest. The NGA uses the VNIIRS scale to rate videos with subjective interpretability. VNIIRS rating provides a meaningful way of organizing video browsing and search. Manually annotating videos with VNIIRS rating however, is very tedious. We propose to develop an automated tool which uses several cues such as mo ...

Over the Horizon Radar (OTHR) has been a deployed capability for over 3 decades. OTHR uses the ionosphere to reflect HF radar signals in order to illuminate objects (potential targets) beyond the horizon, giving it a potential effective range of several hundred to a few thousand kilometers. Understanding how the HF radar signals interact and reflect off the ionosphere is crucial to accurate target ...