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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. 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
  2. Production of Chemical Reagents for Prompt-Agent-Defeat Weapons

    SBC: NALAS ENGINEERING SERVICES INC            Topic: DTRA14B001

    Nalas Engineering and Johns Hopkins University collaborated in a Phase I STTR program to study reactive mixtures of HI3O8 and nanocomposite fuels previously developed by the Weihs Group. These fuel/oxidizer mixtures are uniquely able to simultaneously produce heat and biocidal iodine gas, a combination designed to destroy biological weapons. The team at Nalas focused on evaluating conditions for p ...

    STTR Phase II 2017 Department of DefenseDefense Threat Reduction Agency
  3. Semantic Parsing and role Labeling In Combination Effort (SPLICE)

    SBC: DECISIVE ANALYTICS CORPORATION            Topic: DTRA14B003

    To Counter Weapons of Mass Destruction (CWMD), DTRA must analyze data from numerous sources about a diverse set of technologies and activities. The extreme diversity in content and the volume of DTRAs data combine to produce one of the most challenging analysis problems in the government. The CWMD mission therefore requires deep analysis - an in-depth understanding of all available data and correl ...

    STTR Phase II 2017 Department of DefenseDefense Threat Reduction Agency
  4. 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
  5. 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
  6. Combat Systems of the Future

    SBC: Advanced Systems/Supportability Engineering Technologies And Tools, Inc.            Topic: N05149

    The S-351 mini-sub is a prototype of the Dry Combat Submersible (DCS). This prototype was established as a means of risk reduction prior to a full commitment to the DCS program. Both of these platforms have an operational need to transit with minimum operator fatigue safely to a pre-defined point and covertly deploy and retrieve SEALS. To meet these operational needs, these platforms require upgra ...

    STTR Phase II 2017 Department of DefenseSpecial Operations Command
  7. System for Nighttime and Low-Light Face Recognition

    SBC: Systems & Technology Research LLC            Topic: SOCOM18A001

    Face recognition performance using deep learning has seen dramatic improvements in recent years. This improvement has been fueled in part by the curation of large labeled training datasets with millions of images of hundreds of thousands of subjects.This results in effective generalization for matching over pose, illumination, expression and age variation, however these datasets have traditionally ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  8. Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia

    SBC: HVMN Inc.            Topic: SOCOM17C001

    In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  9. Human Performance Optimization

    SBC: REJUVENATE BIO INC            Topic: SOCOM17C001

    Special Operations Forces (SOF) are an integral aspect of the US military. SOF operators are among the most elite and highly qualified individuals in the U.S. military. As such, extraordinary physical and mental demands are placed upon them to excel in extreme environments for extended periods of time. This unrelenting cycle of combat deployments and intense pre-deployment training shortens the fu ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  10. Data Driven Intent Recognition Framework

    SBC: OTHER LAB, INC.            Topic: NSF13599

    A critical aspect of exoskeleton control that has to date introduced a performance limitation is the ability of the exoskeleton to recognize the intent of the operator so it can apply assistance to their desired motion. This intent recognition effort is typically solved using ad-hoc methods where subject matter experts make design decisions and tune transitions to identify intended maneuvers as re ...

    STTR Phase II 2016 Department of DefenseSpecial Operations Command
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