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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY21 is not expected to be complete until September, 2022.

Download all SBIR.gov award data either with award abstracts (290MB) or without award abstracts (65MB). A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.

  1. Boost- A System to Suppress False Alarms from Automated Target Recognizers

    SBC: Seed Innovations, LLC            Topic: NGA181003

    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 ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  2. Video to Feature Data Association and Geolocation

    SBC: Novateur Research Solutions, LLC            Topic: NGA181007

    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 ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  3. Deep-False Alarm Suppression Technique (D-FAST)

    SBC: Deep Learning Analytics, Llc            Topic: NGA181003

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

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  4. Low-Shot Detection in Remote Sensing Imagery

    SBC: Etegent Technologies, Ltd.            Topic: NGA172002

    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 ...

    SBIR Phase II 2018 Department of DefenseNational Geospatial-Intelligence Agency
  5. Low-Shot Detection in Remote Sensing Imagery

    SBC: Novateur Research Solutions, LLC            Topic: NGA172002

    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 ...

    SBIR Phase II 2018 Department of DefenseNational Geospatial-Intelligence Agency
  6. Asynchronous Active 3D Imaging

    SBC: SCIX3 LLC            Topic: NGA183001

    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 ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  7. Asynchronous Multi-transmitter Multi-aperture Synthetic 3D Imaging System

    SBC: VOXTEL, INC.            Topic: NGA183001

    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 ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  8. Automating Procedural Modeling of Buildings from Point Cloud Data

    SBC: Dignitas Technologies, LLC            Topic: NGA183002

    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 ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  9. SURFER: SAR Unsupervised and Robust Feature ExtractoR

    SBC: THE DESIGN KNOWLEDGE COMPANY            Topic: NGA191001

    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 ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  10. Collaborative Recommender System for Spatio-Temporal Intelligence Documents

    SBC: RAJI BASKARAN LLC            Topic: NGA191005

    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 ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
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