Award Data

Seed Innovations and subcontractor BIT Systems, a division of CACI International, apply our experience in machine learning, data analytics andimage processing to accomplish the research for the SBIR topic: Suppression of false alarms in Automated Target Recognizers (ATR) that useMachine Learning. With the amount of available imagery data increasing and adversaries vehicles and tactics becoming mor ...

This SBIR Phase I project proposes a probabilistic approach to determine a vehicles location using onboard video sensors and foundationalmap data. The system does not rely on only one type of information source, instead it combines proposals from a variety of locationestimators to find a vehicles location in GPS-denied environments.The system takes advantage of recent advancements in computer visi ...

Deep Learning Analytics (DLA) will develop the Deep-False Alarm Suppression Technique (D-FAST) algorithm that uses state of the art and

With the ever-growing number of imaging satellites in orbit the job of an analyst will change from eyes on pixels to analysis of informationfrom imagery thanks to automated image processing like object detection and change detection. Object detection algorithms have advancedto near human performance given that there is sufficient labeled data on which to train; however, obtaining this data is cost ...

This SBIR Phase II project will develop biologically inspired computational models and algorithms to enable low-shot and one-shot detectionof objects-of-interest in remote sensing imagery. The Phase II effort will build upon our Phase I work including multi-scale representationlearning framework and deep-learning based feature extraction and matching techniques for low-shot target detection. The P ...

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 ...

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 ...

The NGA requires an automatic, unsupervised SAR feature extraction (AUFE) technique, that can ultimately be deployed for geospatial analysis, modeling, and target detection. Our proposed “SAR Unsupervised and Robust Feature ExtractoR” (SURFER) solution includes in Phase I: (1) a sound and deterministic assessment of the underlying RF phenomenology and SAR processing theoretical basis for effec ...

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 ...