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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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Logistics Augmented Reality Real-time Efficiency Enhancement System
SBC: INTELLISENSE SYSTEMS INC Topic: DLA181001To address the DLAs need for the implementation of augmented reality (AR) in DLAs procurement, logistics, and distribution processes, Intellisense Systems, Inc. (ISS) proposes to develop a new Logistics Augmented Reality Real-Time Efficiency Enhancement (LARREE) system. LARREE is based on novel ultra-low-cost infrastructure enhancements for real-time tracking, using interoperable software database ...
SBIR Phase I 2018 Department of DefenseDefense Logistics Agency -
Reverse Engineering and Manufacturing of Alternative Display Equipment
SBC: INTELLISENSE SYSTEMS INC Topic: DLA182004To address the Defense Logistics Agency (DLA)s need for KWD-ML-4-115AL alternative supply sources, Intellisense Systems, Inc. (ISI) proposes to develop a new Reverse Engineering and Manufacturing of Alternative Display Equipment (RE-MADE) process specifically to reverse engineer (RE) the KWD-ML-4-115AL display to improve product availability and increase competition. The proposed RE process is bas ...
SBIR Phase I 2018 Department of DefenseDefense Logistics Agency -
Tamper Resistant/Anti-Counterfeit Package Labeling
SBC: Dimensional Defense Corporation Topic: DLA163003A newly developed technology and process applied to sealing packages provides enhanced features in authenticating commodities where anti-counterfeiting and anti-tampering security may be required. This novel sealing method used in conjunction with a unique software-based scan tool each afford unprecedented screening capabilities of multiple packages at vastly increased distance. This technology an ...
SBIR Phase II 2018 Department of DefenseDefense Logistics Agency -
Reverse Engineering Technical Data Packages for Development of Alternate Sources of Supply for DLA NSNs
SBC: SPECTRAL LABS INCORPORATED Topic: DLA171002During Phase II, Spectral Labs proposes using our multi-disciplined engineering, quality assurance, and production staff to complete reverse engineering of the NSN 6130-015487556 Battery Charger, P/N RF-5853-CH106 in order to become an approved source. Participating in this program will provide Spectral Labs with the experience to pursue future business with the DLA Value Management Unit. In addit ...
SBIR Phase II 2018 Department of DefenseDefense Logistics 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 -
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 -
Automated Assessment of Urban Environment Degradation for Disaster Relief andReconstruction
SBC: TOYON RESEARCH CORPORATION Topic: NGA181004Toyon Research Corp. proposes development of a system that automates disaster assessment based on fusion of overhead and ground-basedimages, video, and other data. In Phase I, we will investigate various possible data sources and the benefits of fusing the data in automatedanalysis. We will select and curate data for processing in a Phase I feasibility study. Damage assessment will be performed in ...
SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency