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Award Data
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.
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Botnet Analytics Appliance (BNA)
SBC: MILCORD LLC Topic: HSB061008Recent 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 -
Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery
SBC: TOYON RESEARCH CORPORATION Topic: 1On 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 -
Algorithms for Look-down Infrared Target Exploitation
SBC: SIGNATURE RESEARCH, INC. Topic: 1Signature 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 -
Production of Chemical Reagents for Prompt-Agent-Defeat Weapons
SBC: NALAS ENGINEERING SERVICES INC Topic: DTRA14B001Nalas 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 -
Innovative Mitigation of Radiation Effects in Advanced Technology Nodes
SBC: MICROELECTRONICS RESEARCH DEVELOPMENT CORPORATION Topic: DTRA16A003Micro-RDC has developed portable radiation effects test structures that scale to new process nodes.These structures will enable the investigation of the effects of radiation on the new technology from the material processing level as well as the circuit level.Fabricating the chosen structures and the refinement of software to extract the model parameters will be completed in this effort.A suite of ...
STTR Phase II 2018 Department of DefenseDefense Threat Reduction Agency -
Semantic Models for the Identification of Laboratory Equipment (SMILE)
SBC: CHARLES RIVER ANALYTICS, INC. Topic: DTRA19B002Military 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 -
Multimode Organic Scintillators for Neutron/Gamma Detection
SBC: RADIATION MONITORING DEVICES, INC. Topic: DTRA19B003There 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 -
Hardened, Optically-Based Temperature Characterization of Detonation Environments
SBC: SA PHOTONICS, LLC Topic: DTRA19B001Improving 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 -
Compact Laser Drivers for Photoconductive Semicond
SBC: SCIENTIFIC APPLICATIONS & RESEARCH ASSOCIATES, INC. Topic: DTRA16A004For 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 -
Bounding generalization risk for Deep Neural Networks
SBC: Euler Scientific Topic: NGA20A001Deep 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