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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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Marburg Virus Prophylactic Medical Countermeasure
SBC: MAPP BIOPHARMACEUTICAL, INC. Topic: CBD18A002There are currently no vaccines or therapeutics available for Marburg Virus Disease (MVD). Given the specter of weaponization and the terriblemorbidity and high mortality rate of MVD, this represents a critical threat to the operational readiness of the Warfighter. While traditionalvaccines have proven to be a huge contribution to public health, they do have some limitations especially in the cont ...
STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense -
Fusion of VMS and Radiation Sensor Data for Real-Time Identification and Tracking
SBC: SILVERSIDE DETECTORS INC Topic: HSB0181010Traditionally, implementation of dedicated, continuous nuclear and radiological monitoring systems for identifying and tracking nuclear materials out of regulatory control is associated with high operational burdens. Although video and images from cameras are helpful in assessing threats, the raw, unstructured data require time-intensive human interaction to extract the relevant actionable informa ...
SBIR Phase I 2018 Department of Homeland Security -
Tracking Nuclear Threats in Security Camera Networks (TNT-SCAN)
SBC: CHARLES RIVER ANALYTICS, INC. Topic: HSB0181010The implementation of continuous nuclear and radiological monitoring systems enabling the automatic detection and tracking of potential nuclear threats is traditionally associated with a high operational burden. Sensors typically have to be monitored by dedicated personnel, who must investigate detection events in a timely manner; however, high nuisance alarm rates can rapidly overwhelm already-ta ...
SBIR Phase I 2018 Department of Homeland Security -
Generalized Change Detection to Cue Regions of Interest
SBC: FeatureX, Inc. Topic: NGA181006Generalized change detection is a critical capability to mitigate the need for massive human inspection of the rapidly expanding volume ofglobal overhead satellite imagery. Current optical change detection approaches focus on fully specified systems to detect a predefined set ofchanges, and effective approaches for generalized change detection have not yet been demonstrated. We propose to build a ...
SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency -
Marburg Virus Prophylactic Medical Countermeasure
SBC: Flow Pharma, Inc. Topic: CBD18A002Flow Pharma, Inc. is a biotechnology company in the San Francisco Bay Area developing fully synthetic cytotoxic T lymphocyte (CTL)stimulating peptide vaccines for Marburg virus. The FlowVax vaccine platform allows us to create dry powder formulations of biodegradablemicrospheres and TLR adjuvants incorporating class I and class II T cell epitopes. FlowVax vaccines can be designed for delivery by i ...
STTR Phase I 2018 Department of DefenseOffice for Chemical and Biological Defense -
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 -
Low-Shot Detection in Remote Sensing Imagery
SBC: TOYON RESEARCH CORPORATION Topic: NGA181010The National Geospatial-Intelligence Agency (NGA) ingests and analyzes raw imagery from multiple sources to form actionable intelligenceproducts that can be disseminated across the intelligence community (IC). To effectively meet these demands NGA must continue to improveits automated and semi-automated methods for target detection and classification. Of particular concern is furthering NGA's abil ...
SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency -
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 -
Generalized Change Detection to Cue Regions of Interest
SBC: TOYON RESEARCH CORPORATION Topic: NGA181006Toyon Research Corporation proposes to research and develop algorithms for generalized change detection, by leveraging and exploringexisting and proven effective traditional and deep learning methods, with a unique 3D reconstruction component. The vast majority of themassive amounts of imagery data will have small pixel level differences due to a multitude of unimportant changes: minor misregistra ...
SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency -
Variational Object Recognition and Grouping Network
SBC: INTELLISENSE SYSTEMS INC Topic: NGA181005To address the National Geospatial-Intelligence Agency (NGA) need for overhead imagery analysis algorithms that provide uncertaintymeasures for object recognition and aggregation, Intellisense Systems, Inc. (ISS) proposes to develop a new Variational Object Recognition andGrouping Network (VORGNet) system. It is based on the innovation of implementing a Bayesian convolutional neural network (CNN) ...
SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency