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The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.
Download all SBIR.gov award data either with award abstracts (290MB)
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A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.
Low-Shot Detection in Remote Sensing ImagerySBC: TOYON RESEARCH CORPORATION Topic: NGA181010
The 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
Miniature Intelligent Spectral AnalyzerSBC: Physical Optics Corporation Topic: HSB0181003
To address the DHS need to rapidly detect radio interference of critical radio frequency (RF) communications channels utilized by first responders, Physical Optics Corporation (POC) proposes to develop a new Miniature Intelligent Spectral Analyzer (MISCAN) device based on a combination of commercial off-the-shelf (COTS) electronic components in a custom software-defined configuration along with in ...SBIR Phase I 2018 Department of Homeland Security
Remote Phone Locator for Improved Emergency RescueSBC: Physical Optics Corporation Topic: HSB0181002
To address the Department of Homeland Security (DHS) need for a cell phone location finder for maritime and remote search and rescue (SAR), Physical Optics Corporation (POC) proposes to develop a new REmote Phone Locator for Improved Emergency Rescue (REPLIER). REPLIER leverages novel techniques recently developed at POC to extend the range of cellular communications and integrate commercial cellu ...SBIR Phase I 2018 Department of Homeland Security
SHAPE-BASED GENERALIZATION BOUNDS FOR DEEP LEARNINGSBC: GEOMETRIC DATA ANALYTICS Topic: NGA20A001
We propose to develop a theoretical understanding of the relationship between intrinsic geometric structure in both training and latent data and characteristics of functions learned from that data for deep neural network (DNN) architectures. Along the way we propose to also understand the structure of the neural networks that are best trained on a given data set. Both of these theories will lead t ...STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
Soft Targets and Crowded Places SecuritySBC: KARAGOZIAN & CASE, INC. Topic: DHS201004
To address the Department of Homeland Security (DHS) Cybersecurity and Infrastructure Security Agency (CISA) requirements and strategic intent, Karagozian and Case, Inc. (K&C) proposes to develop a SECURITY MITIGATION ASSESMENT OF RISKS AND THREATS (SMART) software application for SOFT TARGETS AND CROWDED PLACES (ST-CP) which leverages advanced Geographical Information Systems (GIS) mapping softwa ...SBIR Phase I 2020 Department of Homeland Security
Targeted Surface Interrogation Scanning SystemSBC: INTELLISENSE SYSTEMS INC Topic: DHS201007
To address the DHS's need for a quick and efficient targeted surface interrogation technique to locate and detect trace residues of interest, including explosives and illicit drugs, on carry-on baggage and items, Intellisense Systems, Inc. proposes to develop a new rapid Targeted Surface Interrogation Scanning (TASIS) system, based on ultraviolet Raman spectroscopy and fast data processing/renderi ...SBIR Phase I 2020 Department of Homeland Security
Variational Object Recognition and Grouping NetworkSBC: INTELLISENSE SYSTEMS INC Topic: NGA181005
To 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