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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. Botnet Analytics Appliance (BNA)

    SBC: MILCORD LLC            Topic: HSB061008

    Recent reports indicate the activity of more than 6,000 botnet C and C servers. 70 million zombies are responsible for 80 percent of SPAM. Given the exponential growth of the botnet threat, the security of our nation s cyber infrastructure demand automated botnet activity monitoring solutions. In Phase I, Milcord developed a feasibility prototype of a Bayesian Activity Monitor for Botnet Defense. ...

    STTR Phase II 2007 Department of Homeland Security
  2. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  3. 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
  4. Semantic Models for the Identification of Laboratory Equipment (SMILE)

    SBC: CHARLES RIVER ANALYTICS, INC.            Topic: DTRA19B002

    Military operators must identify and catalogue the equipment they find when inspecting laboratory facilities. This information is used to determine the lab’s capabilities, including the lab’s potential for building weapons of mass destruction. Currently, operators use computer vision algorithms to help them classify equipment in pictures of laboratory environments. Unfortunately, current image ...

    STTR Phase I 2020 Department of DefenseDefense Threat Reduction Agency
  5. Multimode Organic Scintillators for Neutron/Gamma Detection

    SBC: RADIATION MONITORING DEVICES, INC.            Topic: DTRA19B003

    There is significant interest in multi-functional materials enabling gamma-ray spectroscopy, neutron/gamma pulse shape discrimination (PSD), ultra-fast response, and time-of-flight (TOF) neutron detection. These materials would be used in a variety of mission scenarios for the localization and monitoring of special nuclear materials. Commercial inorganic scintillators offer some of these character ...

    STTR Phase I 2020 Department of DefenseDefense Threat Reduction Agency
  6. Hardened, Optically-Based Temperature Characterization of Detonation Environments

    SBC: SA PHOTONICS, LLC            Topic: DTRA19B001

    Improving the effectiveness of counter-WMD operations requires improved understanding of weapon-target interaction. Specifically, time-resolved measurements of temperature and composition are required to allow temporal evolution of a detonation fireball. To address this need, SA Photonics will develop MONITOR, a laser-based temperature diagnostic that will enable wide dynamic range temperature mea ...

    STTR Phase I 2020 Department of DefenseDefense Threat Reduction Agency
  7. Compact Laser Drivers for Photoconductive Semicond

    SBC: SCIENTIFIC APPLICATIONS & RESEARCH ASSOCIATES, INC.            Topic: DTRA16A004

    For effective protection against radiated threats, it is important to understand not only the physics of the threats, but also to quantify the effects they have on mission-critical electrical systems. Radiated vulnerability and susceptibility testing requires delivery of high peak power and peak electric fields to distant targets. The most practical solution to simulate such environments on large ...

    STTR Phase II 2018 Department of DefenseDefense Threat Reduction Agency
  8. Bounding generalization risk for Deep Neural Networks

    SBC: Euler Scientific            Topic: NGA20A001

    Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  9. Algorithms for Look-down Infrared Target Exploitation

    SBC: SIGNATURE RESEARCH, INC.            Topic: NGA18A001

    The multidisciplinary area of GEOINT is changing and becoming more complex. A major driver of innovation in GEOINT collection and processing is artificial intelligence (AI). AI is being leveraged to help accomplish spatial analysis, change detection, and image or video triage tasks where filtering objects of interest from large volumes of data is critical. NGA is confronting the changing GEOINT l ...

    STTR Phase II 2020 Department of DefenseNational Geospatial-Intelligence Agency
  10. Mixed Elpasolite Scintillators

    SBC: RADIATION MONITORING DEVICES, INC.            Topic: DTRA18B003

    The goal of this program is to develop the mixed elpasolite scintillators in order to achieve an energy resolution of  (≤ 2.5% (approaching 2%) at 662 keV for crystal sizes of up to 2 inch by 2 inch.  In this project we will investigate compositional changes in selected mixed-elpasolite(s) in order to achieve very high energy resolution.  By incorporating 6Li, neutron detection will also be t ...

    STTR Phase II 2020 Department of DefenseDefense Threat Reduction Agency
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