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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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NGAflix: a cloud-based adaptive bitrate video processing and distribution system
SBC: KITWARE INC Topic: NGA181002The large volume of full motion video from unmanned aerial vehicles, along with other data from various sensors creates resource andengineering challenges in managing, processing and distributing that data. Law enforcement and intelligence work require videos in locationsfar from where they were recorded, and need multiple sensor streams to be synchronized for search, filtering, and transformation ...
SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency -
Low-Shot Alternate Viewpoint Analogies
SBC: KITWARE INC Topic: NGA181008Overhead imagery analysts spend their time scouring aerial and satellite imagery looking for objects based on example images. Collectingexample imagery of our adversaries newest military hardware is often challenging. The only examples we have may be from open sourceintelligence at air shows or military parades or from limited clandestine collections. Often, only a small set of ground-based imager ...
SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency -
Densely Connected Neural Networks for Remote Sensing
SBC: LYNNTECH INC. Topic: NGA181010The objective of this project is to design a software architecture based on densely-connected neural network to perform automatic targetsegmentation and recognition using training datasets of limited size (low-shot). Deep learning architectures have proved to be extremelyeffective at object detection and recognition, but such capability comes at the cost of having large labeled datasets. Such data ...
SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency -
Memory Instrumentation and Performance Simulation (MIPS)
SBC: ATC-NY INC Topic: DTRA172003Next-generation high-performance computing (HPC) hardware, such as the Intel Xeon Phi Knights Landing Many-Integrated-Core processor, provide new deep memory architectures that offer the promise of increased performance. The challenge in taking full advantage of this architecture is selecting which data structures will be placed in the high-bandwidth memory. Optimizing data structure placement in ...
SBIR Phase I 2018 Department of DefenseDefense Threat Reduction Agency -
Low-Cost Sensing Array for Infrasound
SBC: CREARE LLC Topic: DTRA172001Infrasound and seismic measurements are used by DTRA and the DoD for nuclear test monitoring, terrorist blast forensics, battle damage assessment, and environmental monitoring. However, these long wavelength physical signals are typically recorded through single-point sensors or sparse low density arrays. As a result, the critical signals of interest are often corrupted or masked by noise or inter ...
SBIR Phase I 2018 Department of DefenseDefense Threat Reduction Agency -
Safe High-Energy Long-Life (SHELL) Solid-State Ultracapacitors
SBC: LYNNTECH INC. Topic: DTRA172005In order to reduce DTRAs dependence on batteries and their associated logistics train, advanced power supplies, which are able to charge quickly and work in a wide variety of environmental conditions, and are reusable over many charge-discharge cycles without loss of performance, are greatly required. Lynntech proposes to develop safe, high energy, long-life (SHELL) solid-state ultracapacitors by ...
SBIR Phase I 2018 Department of DefenseDefense Threat Reduction Agency -
Non-saturating, high-sensitivity military pocket dosimeter
SBC: PROPORTIONAL TECHNOLOGIES, INC. Topic: DTRA172007During this Phase I effort, Proportional Technologies, Inc. will develop non-saturating components for a military battlefield dosimeter based on ionization chamber technology, which will ultimately be combined with low-dose sensors in Phase II for a final product that is both highly sensitive, accurate, and non-saturating in the event of a nuclear blast or other high-dose scenario. The proposed hi ...
SBIR Phase I 2018 Department of DefenseDefense Threat Reduction Agency -
Semantic Analysis Technologies for the Identification of Dual Use Research of Concern (STIR)
SBC: KNOWLEDGE BASED SYSTEMS INC Topic: DTRA172004Knowledge Based Systems, Inc. (KBSI) proposes to design and develop Semantic Analysis Technologies for the Identification of Dual Use Research of Concern (STIR). The proposed STIR will process scientific documents using semantic technologies and inference algorithms to identify potential for Dual Use Research of Concern (DURC). The focus will be on 15 high consequence pathogens and toxins and seve ...
SBIR Phase I 2018 Department of DefenseDefense Threat Reduction Agency -
A Robust, Machine Independent, Software Toolkit for Topology Aware Process Mapping on Distributed Memory HPC Architectures
SBC: CONTINUUM DYNAMICS INC Topic: DTRA172002A significant performance gap exists between the theoretical number of Floating Point Operations (FLOPS) that a HPC machine is capable of sustaining and the number of FLOPS realized by real-world HPC applications. One of the principle reasons for this gap is the parasitic work that computational processes must do to communicate with one another. It has been shown that this communication work can b ...
SBIR Phase I 2018 Department of DefenseDefense Threat Reduction Agency -
Satellite Low-Shot Augmented Object Detection (SALSA)
SBC: KITWARE INC Topic: NGA172002The recent widespread use of overhead sensors, and their ability to provide continuous streams of imagery for intelligence, surveillance and reconnaissance (ISR) missions, has generated a critical need for high-fidelity, automated object detection systems. For intelligence analysts, searching large volumes of imagery with vast spatial and temporal extent can be extremely time consuming and tedious ...
SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency