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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

  1. Monitoring and Inspecting Dirty Nukes Including Generating Heatmaps of Terrain (MIDNIGHT)

    SBC: Charles River Analytics, Inc.            Topic: HSB0191010

    A successful weapon of mass destruction (WMD) terrorist attack against the United States would have a profound and potentially catastrophic impact on our nation. It is imperative to be able to quickly, efficiently, and effectively localize radiological threats in a wide array of unstructured environments to detect and deter such an event. In recent years, man-portable radiation detectors have beco ...

    SBIR Phase I 2019 Department of Homeland Security
  2. Networked Aerial Vehicle for Automated Radiation Clearing (NAVARC)

    SBC: Physical Sciences Inc.            Topic: HSB0191010

    Physical Sciences Inc. (PSI) proposes to develop the Networked Aerial Vehicle for Automated Radiation Clearing (NAVARC) to perform an autonomous search for radiological threats in a complex 3-D environment. The PSI-developed InstantEye unmanned aerial vehicle (UAV) will navigate using a series of optimized waypoints to minimize the time required to fully search an area and inspect objects. Detecti ...

    SBIR Phase I 2019 Department of Homeland Security
  3. Cybersecurity Peer-to-Peer Knowledge/Lessons Learned Tool

    SBC: INFERLINK CORPORATION            Topic: HSB0191006

    The increasing number of breaches and hacks against organizations demands new and more effective ways to provide defense. Currently, most defense activities, such as monitoring, analysis, forensics, and remediation are done within house. This is unfortunate because the external knowledge and experience of others outside the organization cannot easily be leveraged. Our proposal focuses on the desig ...

    SBIR Phase I 2019 Department of Homeland Security
  4. Dynamical Network Models for Mission Risk Assessment of Emergency Response Systems

    SBC: Achilles Heel Technologies, LLC            Topic: HSB0191007

    The integration of new cyber technologies in emergency response systems can allow profound improvements in system performance, but also expose the systems to systemic security and privacy risks.Thus, there is a critical need for design-time risk-assessment tools for emergency response systems, which allow evaluation and mitigation of threat impacts across their heterogeneous cyber and physical com ...

    SBIR Phase I 2019 Department of Homeland Security
  5. Power and Rechargeable Battery Interface Smart Module

    SBC: Intellisense Systems, Inc.            Topic: HSB0191003

    To address the DHS need for a module that can power/charge and provide effective power management of all on-body electronics including sensors, communications systems, and peripheral devices for all first responder mission areas, Intellisense Systems, Inc. (ISI) proposes to develop a new Power and Rechargeable Battery Interface Smart Module (PRISM). This proposed technology is based on a novel mod ...

    SBIR Phase I 2019 Department of Homeland Security
  6. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On 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
  7. Algorithms for Look-down Infrared Target Exploitation

    SBC: Signature Research, Inc.            Topic: 1

    Signature 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
  8. GEOFF: Geo-location from Edges, Objects, Foundational data, and a Filter

    SBC: Scientific Systems Company Inc.            Topic: NGA181007

    Ground vehicles with navigation capability (e.g., GPS) can index into foundation data (e.g., Google Maps) to gain situational awareness abouttheir surroundings. When GPS and RF navigation sources are degraded, maintaining situational awareness requires an alternative navigationsource. One alternative source is the foundation data itself. The data contain objects at known 3D locations, which projec ...

    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. 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
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