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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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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 -
Bounding generalization risk for Deep Neural Networks
SBC: Euler Scientific Topic: NGA20A001Deep Convolutional Neural Networks (DCNNs) have become ubiquitous in the analysis of large datasets with geometric symmetries. These datasets are common in medicine, science, intelligence, autonomous driving and industry. While analysis based on DCNNs have proven powerful, uncertainty estimation for such analyses has required sophisticated empirical studies. This has negatively impacted the effect ...
STTR Phase II 2022 Department of DefenseNational Geospatial-Intelligence Agency -
Data Driven Intent Recognition Framework
SBC: OTHER LAB, INC. Topic: NSF13599A 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 -
Human Performance Optimization
SBC: REJUVENATE BIO INC Topic: SOCOM17C001Special 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 -
Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia
SBC: HVMN Inc. Topic: SOCOM17C001In 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 -
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 -
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 -
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 -
Multi-Dimensional Event Sourcing & Correlation- Publicly Available Information (PAI) (MDESC-P)
SBC: PROGRAMS MANAGEMENT ANALYTICS & TECHNOLOGIES INC Topic: SOCOM22DST01Multi-Dimensional Event Sourcing & Correlation - Publicly Available Information (PAI) (MDESC-P) will support collection jointly across disparate PAI sources with coordinated cueing of more constrained intelligence, surveillance, target acquisition, and reconnaissance (ISTAR) sources. The primary objective for MDESC-P is to deliver a scalable and automated PAI collection management solution using a ...
STTR Phase I 2022 Department of DefenseSpecial Operations Command -
Population Behavioral Analysis at Scale, AOR Modeling
SBC: DEEP LABS INC Topic: SOCOM22DST01Deep Labs recognizes USSOCOM’s challenge to process multiple data and communications inputs for optimized decision making, and to support rapid on-the-move abilities to learn and communicate knowledge to enhance tactically relevant situational awareness in peer/near peer environments. Deep Labs has proven this capability across complex challenges in the world’s largest commercial enterprises a ...
STTR Phase I 2022 Department of DefenseSpecial Operations Command