You are here

Award Data

For best search results, use the search terms first and then apply the filters
Reset

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. Generative Modeling of Multispectral Satellite Imagery

    SBC: NOVATEUR RESEARCH SOLUTIONS LLC            Topic: DTRA22D001

    This STTR Phase I project proposes novel deep learning models for generating realistic multi-spectral remote sensing imagery, specifically in the infrared (IR) and near-infrared (NIR) bands. The proposed system enables synthesis of semantically realistic imagery and provides parametric control of synthesizing objects-of-interest, type of terrain and land cover, time or season, weather, cloud cover ...

    STTR Phase I 2023 Department of DefenseDefense Threat Reduction Agency
  2. Generative Modeling of Multispectral Satellite Imagery

    SBC: Applied Research In Acoustics LLC            Topic: DTRA22D001

    To address the challenge DTRA faces in identifying rare objects of interest to defeat improvised threat networks using multispectral imagery, small business ARiA and research institution Michigan Technological University (MTU) will develop and demonstrate the feasibility of the Generative Augmentation Process (GAP). The Phase I effort will (1) conduct a proof-of-concept study for GAP by developing ...

    STTR Phase I 2023 Department of DefenseDefense Threat Reduction Agency
  3. Wide Area Distributed Algorithms for Cooperative Source Identification, Characterization, and Localization

    SBC: THE PROBITAS PROJECT, INC.            Topic: DTRA21B003

    Current radiation detection algorithms are based on the concept that each detector operates independently. The Probitas Project, Inc. (Probitas) and the Lawrence Berkeley National Laboratory (LBNL) propose to show the benefits of data fusion to improve the identification, localization, and characterization of a radioactive source in a complex scene as compared to a singular detector algorithm. We ...

    STTR Phase I 2022 Department of DefenseDefense Threat Reduction Agency
  4. Numerically Inspired Deep Neural Nets for Chemically Reacting Flows

    SBC: APPLIED SIMULATIONS INC            Topic: DTRA21B002

    The project will develop numerically inspired deep neural nets (NINNs) in order to replace the stiff ordinary differential equation (SODE) solvers currently being used to integrate chemical species in high-fidelity computational fluid dynamics simulations. Unlike traditional deep neural nets, the architectures and optimization strategies used to learn the physics of a problem will be based on the ...

    STTR Phase I 2022 Department of DefenseDefense Threat Reduction Agency
  5. ECCCHO: Effective Combat Casualty Care Handoff Operations

    SBC: TIER 1 PERFORMANCE SOLUTIONS LLC            Topic: DHA17B002

    According to the Joint Commission, approximately 70% of sentinel events in medical care are related to communication mishaps, and despite regular and frequent occurrence, poor communication during patient handoffs (i.e., transfer of patient care information, responsibility, and authority from one provider to another) remains a major contributor to medical errors (Nether, 2017; The Joint Commission ...

    STTR Phase II 2021 Department of DefenseDefense Health Agency
  6. Improved Identification of the function of Novel and Partially Occluded Laboratory Equipment

    SBC: NOVATEUR RESEARCH SOLUTIONS LLC            Topic: DTRA19B002

    This STTR Phase II project proposes development of a statistical relational learning framework for identification of the function of laboratory equipment from imagery. The proposed framework uses semantic reasoning to incorporate evidence from multiple classifiers and feature extractors, domain knowledge, and scene context for scene understanding and labeling. The Phase II effort will focus on dev ...

    STTR Phase II 2021 Department of DefenseDefense Threat Reduction Agency
  7. Urbanscape: Single Shot Multi-Task 3D Reconstruction

    SBC: DZYNE TECHNOLOGIES, LLC            Topic: DTRA18B001

    Hazard assessment tools that model the transport and dispersion of Chemical, Biological, Radiological, Nuclear and Explosive (CBRNE) materials through urban areas are only as good as the 3D models that inform the physics model. Maintaining accurate, up-to-date 3D models of urban areas is challenging. Even in the commercial world, urban construction and demolition may result in the models created a ...

    STTR Phase II 2020 Department of DefenseDefense Threat Reduction Agency
  8. Improved Identification of the function of Novel and Partially Occluded Laboratory Equipment.

    SBC: NOVATEUR RESEARCH SOLUTIONS LLC            Topic: DTRA19B002

    This STTR Phase 1 project proposes development of a statistical relational learning framework for identification of the function of laboratory equipment from imagery. The proposed framework uses semantic reasoning to incorporate evidence from multiple classifiers and feature extractors, domain knowledge, and scene context for scene understanding and labeling. The Phase I effort will focus on imple ...

    STTR Phase I 2020 Department of DefenseDefense Threat Reduction Agency
  9. 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
  10. Virus-Like Particle Based pan-Marburgvirus Vaccine

    SBC: LUNA INNOVATIONS INCORPORATED            Topic: CBD18A002

    Marburg virus (MARV) is a filamentous enveloped non-segmented negative sense RNA virus. This viruse is considered to be extremelydangerous with case fatality rates as high as 88-90%. Extensive efforts have gone towards effective vaccines for MARV prevention, however,none have been successfully established as licensed vaccines. Glycoprotein (GP) is the only surface protein of MARV. There are substa ...

    STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
US Flag An Official Website of the United States Government