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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.

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. Simultaneous Multiple Object Detection System

    SBC: Semquest, Inc.            Topic: MDA16T006

    An advanced hit detection technology is needed for MDA that can report impacts at hyper-velocities and at multiple hit locations. We present a technology with a high level of performance that leverages decades of hit technology experience and utilizes existing technologies developed under previous efforts. Our technology offers a low latency non-interpolated direct indicator of multiple hit locati ...

    STTR Phase II 2018 Department of DefenseMissile Defense Agency
  2. Developing Software for Pharmacodynamics and Bioassay Studies

    SBC: TConneX Inc.            Topic: DHP16C001

    Thegoal is to develop asoftwaretool that implementsa novelapproach applicableto fitgeneral pharmacologic, toxicology, or other biomedical data, that mayexhibita non-monotonic dose-responserelationship for which thecurrent parametricmodels fail. Thesoftwareexplores dose-responserelationships using both monotonicand non-monotonicmodels,and estimates theassociated doseresponsecurves,which can further ...

    STTR Phase II 2019 Department of DefenseDefense Health Agency
  3. CONTEXTUAL REASONING FOR OBJECT IDENTIFICATION

    SBC: NOVATEUR RESEARCH SOLUTIONS LLC            Topic: MDA15T001

    This project will develop a statistical-relational framework and enabling technologies for context-aware object classification and selection. The proposed framework is capable of reasoning about the scene as a whole while incorporating the entire corpus of available information including features and classification labels from heterogeneous sensors and properties of other objects in the scene. The ...

    STTR Phase II 2018 Department of DefenseMissile Defense Agency
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