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The Award database is continually updated throughout the year. As a result, data for FY21 is not expected to be complete until September, 2022.

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.

  1. Low-Shot Detection in Remote Sensing Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA172002

    Toyon Research Corporation proposes to research and develop algorithms for low-shot object detection, adapting popular techniques to address the complexities inherent in ATR for remote sensing. Traditional object detection algorithms rely on large corpora of data which may not be available for more exotic targets (such as foreign military assets), and therefore, traditional Convolutional Neural Ne ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  2. Miniature Intelligent Spectral Analyzer

    SBC: 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
  3. Advanced Receiver for Distressed Emitter Localization (ARDEL)

    SBC: TOYON RESEARCH CORPORATION            Topic: HSB0181002

    A majority of U.S. adults own a cell phone and are inclined to use it in emergency situations to call for assistance. Unfortunately, in areas where the density of cell towers is low, such as in rural and off-shore environments, the ability of the wireless network to geolocate the origin of the wireless signal is poor to non-existent. Under the proposed effort, Toyon Research Corporation will devel ...

    SBIR Phase I 2018 Department of Homeland Security
  4. Remote Phone Locator for Improved Emergency Rescue

    SBC: 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
  5. Automated and Scalable Analysis of Mobile and IoT Device Firmware

    SBC: RAM LABORATORIES            Topic: HSB0181008

    As Internet of Things (IoT) and mobile devices become increasingly popular and widely used, the security of the firmware running on these devices is paramount.However, due to the lack of an efficient and scalable analysis framework, combined with the increasing pressure to get products to market as quickly as possible, the software running on these devices is never properly checked for security vu ...

    SBIR Phase I 2018 Department of Homeland Security
  6. Bilayer Nanofibers as Wearable Sensors for Detecting Fentanyl Compounds

    SBC: Vaporsens, Inc.            Topic: HSB0181001

    Drug overdose is now the leading cause of death for Americans under 50 years old, with fentanyl claiming more lives than any other drug.Alarmingly, the problem is increasing, with fentanyl overdoses claiming nearly twice as many lives in 2016 compared to 2015.In addition to users, first responders are at risk for coming into contact with fentanyl as they perform their duties.Fentanyl is extremely ...

    SBIR Phase I 2018 Department of Homeland Security
  7. Bayesian Urban Degradation Assessment

    SBC: Intellisense Systems, Inc.            Topic: NGA181004

    To address the NGA need for algorithms that fuse observables from over-flight operations and from ground sources to automatically estimatethe degradation of urban environments due to battle damage or natural disasters, Intellisense Systems, Inc. (ISS) proposes to develop a newBayesian Urban Degradation Assessment (BUDA) software system. It is based on the integration of multiple damage assessment ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  8. Automated Assessment of Urban Environment Degradation for Disaster Relief andReconstruction

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA181004

    Toyon 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
  9. Variational Object Recognition and Grouping Network

    SBC: 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
  10. Blending Ground View and Overhead Models

    SBC: Arete Associates            Topic: NGA181008

    We propose to build ARGON, the ARet Ground-to-Overhead Network. The network will ingest analyst-supplied ground-level imagery ofobjects and retrieve instances of those objects in overhead collections, providing tips back to the analysts. A proprietary method of trainingthe network, leveraging in-house capabilities, data sources, and tools, will be critical to its success. During Phase I, we will p ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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