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The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.

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.

The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.

  1. GEOGENX: target disambiguation through spatiotemporal context

    SBC: VISION SYSTEMS INC            Topic: NGA201004

    Satellite platforms play a critical role in the modern defense and intelligence infrastructure, providing timely, detailed, and readily available imagery to support U.S. national security. An ever present and fundamental requirement for this type of data is automated target detection and recognition, helping to quickly locate and correctly identify targets from vast quantities of image data. Despi ...

    SBIR Phase II 2023 Department of DefenseNational Geospatial-Intelligence Agency
  2. CLOAKT (Classification of Low-shot Objects via Attributed Knowledge Transfer)

    SBC: ETEGENT TECHNOLOGIES, LTD.            Topic: NGA172002

    The intelligence community is faced with an increasingly difficult challenge: the amount of data far outstrips the number of analysts that exploit this data into actionable information. With the ever-growing number of imaging satellites in orbit the job of an analyst will change from eyes on pixels to analysis of information from imagery thanks to automated image processing like object detection a ...

    SBIR Phase II 2021 Department of DefenseNational Geospatial-Intelligence Agency
  3. IMAGINE: Imagery Management through Agile, Geo-Interactive, Natural Embodiment

    SBC: APTIMA INC            Topic: NGA11002

    Overhead imagery analysts employ computer-based software as Electronic Light Tables (ELTs), to perform detailed analysis of aerial images in search of elements of interest. Conventional display design for ELT software requires analysts to take their eyes away from the image they are analyzing to perform routine functions. This interaction overhead typically leads to losses in visual momentum and i ...

    SBIR Phase II 2013 Department of DefenseNational Geospatial-Intelligence Agency
  4. Low-Shot Detection in Remote Sensing Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA172002

    Toyon Research Corporation proposes to develop algorithms that improve the precision and recall of neural networks for low-shot object classification and detection. Our approach is based upon developing a descriptive multi-domain feature representation of the low-shot target as well as the surrounding context. A multi-branch neural network merges the various domains of information to perform accur ...

    SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency
  5. TOFENet – Topographic Features Extraction Network

    SBC: Intelligent Automation, Inc.            Topic: NGA181001

    Topographic features found in ground-based natural images contain information that is useful for a variety of applications including geolocation estimation and navigation. Traditionally, these features have been manually labeled by analysts which is costly and time consuming, especially considering the volume of readily available data. During Phase I, we have demonstrated a novel TOFENet framework ...

    SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency
  6. Generalized Change Detection to Cue Regions of Interest

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA181006

    Toyon proposes to research and develop algorithms for generalized salient change detection, and to incorporate these algorithms into software tools implemented on the cloud. Our approach leverages the two most promising methods from Phase I, both based on supervised learning. The first method is the entropy-based feature vector and corresponding neural network, which we will apply at a coarse sear ...

    SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency
  7. CloudVS: Next Generation Video Services In Cloud Computing

    SBC: Intelligent Automation, Inc.            Topic: NGA181002

    With the explosive growth of Internet of Things (IoT) and mobile communication technologies, media streaming service and applications based on video content have gained remarkable popularity and interest from users. When someone is using their device to record a video, then share that video with friends through a certain website (e.g. Netflix, YouTube), the process may sound simple from the user s ...

    SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency
  8. Automated Assessment of Urban Environment Degradation for Disaster Relief and Reconstruction

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA181004

    Toyon Research Corp. proposes development of a software prototype for automated 3D damage assessment in urban environments. We will document the requirements for the algorithms and software, and optimize or extend the algorithms as needed. We will implement the software prototype, leveraging and integrating existing components where possible and implementing new components as needed. We will qua ...

    SBIR Phase II 2020 Department of DefenseNational Geospatial-Intelligence Agency
  9. Low-shot Using Contextual Knowledge and Ephemeral Search Hierarchy for One-shot Targets (LUCK E SHOT) in Remote Sensing Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA181010

    At a high level, the primary technical objective of the proposed effort is to Identify, obtain, evaluate, and improve datasets; Investigate the use of Meta-Learning to improve the low-shot detection performance of the feed forward network;   Extend research in multi-branch multi-domain embedding networks and semantic layouts for low-shot detection in remote sensing imagery; and Develop and implem ...

    SBIR Phase II 2020 Department of DefenseNational Geospatial-Intelligence Agency
  10. VAST-CQA: Video Annotation and Statistics Toolkit for Crowdsourcing Quality Assessment

    SBC: Intelligent Automation, Inc.            Topic: NGA191002

    The Video-National Imagery Interpretability Rating Scale (VNIIRS) is a task-based scale that reflects observable semantic content in videos. Intelligence agencies such as the NGA use VNIIRS for applications such as efficient storage and retrieval, data browsing, and testing of automated video assessment systems. Existing methods for video quality assessment rely on expert analysts to view and tag ...

    SBIR Phase II 2021 Department of DefenseNational Geospatial-Intelligence Agency
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