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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. Explainable Query Refinement for Human Machine Teaming

    SBC: KITWARE INC            Topic: SOCOM18B001

    The Intelligence, Surveillance and Reconnaissance (ISR) analysts have a challenging task to extract useful information from huge volumes of data from various sources like Full Motion Video (FMV), Wide Area Motion Imagery (WAMI), satellite imagery, Synthetic Aperture Radar (SAR), and others. Modern Machine Learning (ML) algorithms based on deep learning have greatly advanced computer vision, speech ...

    STTR Phase I 2019 Department of DefenseSpecial Operations Command
  2. Inhibiting Prolyl Hydroxylase to Mimic Natural Acclimatization to High Altitude to Improve Warfighter Performance at High Altitude

    SBC: Research Logistics Company            Topic: SOCOM17C001

    Acclimatization is the long-term adjustment that humans experience when exposed for weeks or months to high altitude. Acclimatization is important in this context because a warfighter who is acclimatized to high altitude is immune to high altitude illness, has superior work capacity, and has cognitive function approaching that found at sea level. In other words, the acclimatized warfighter is opti ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  3. Circulating Diagnostic Markers of Infectious Disease

    SBC: PATHOVACS INCORPORATED            Topic: CBD18A001

    The focus of this STTR phase I component is on proof-of-concept studies demonstrating applicability of technical approaches for identificationof circulatory diagnostic markers for infectious disease. Therefore, the primary objective of this project is to determine feasibility of one suchtechnical approach called Proteomics-based Expression Library Screening (PELS), for identification of pathogen-d ...

    STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense
  4. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: SENVOL LLC            Topic: DLA18A001

    The Department of Defense (DoD) has a demand for out-of-production parts to maintain mission readiness of various weapons platforms. Additive manufacturing (AM) is an exciting and promising manufacturing technique that can make out-of-production parts and holds the potential to solve supply chain issues, such as high costs (i.e. for low-volume parts) and sole sourcing risks. The ability of AM to s ...

    STTR Phase I 2018 Department of DefenseDefense Logistics Agency
  5. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: ARCTOS Technology Solutions, LLC            Topic: DLA18A001

    Universal Technology Corporation (UTC) has teamed with the University of Dayton Research Institute (UDRI), Stratonics, and Macy Consulting to demonstrate not only the transitionability into commercial systems, but also to develop the data analytics and monitoring and control requirements to extract the full value fromseveral sensors, including the Stratonics ThermaViz, acoustic and profilometry se ...

    STTR Phase I 2018 Department of DefenseDefense Logistics Agency
  6. Algorithms for Look-down Infrared Target Exploitation

    SBC: SIGNATURE RESEARCH, INC.            Topic: 1

    Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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