Award Data

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The Award database is continually updated throughout the year. As a result, data for FY19 is not expected to be complete until June, 2020.

  1. 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
  2. Low-Shot Detection in Remote Sensing Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA181010

    The 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
  3. Generalized Change Detection to Cue Regions of Interest

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA181006

    Toyon 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
  4. Improving Uncertainty Estimation with Neural Graphical Models

    SBC: MAYACHITRA, INC.            Topic: NGA181005

    Building interpretable, composable autonomous systems requires consideration of uncertainties in the decisions and detections theygenerate. Human analysts need accurate absolute measures of probability to determine how to interpret and use the sometimes noisy resultsof machine learning systems; and composable autonomous systems need to be able to propagate uncertainties so that later reasoningsyst ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  5. 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
  6. 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
  7. 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
  8. Compact, Lightweight Open-Path Cavity RingdownSpectrometry System for UAS Deployment

    SBC: Nikira Labs Inc.            Topic: 841

    TECHNICAL ABSTRACT: In this Small Business Innovative Research (SBIR) program, Nikira Labs Inc. proposes to miniaturize the patented, open-path cavity ringdown spectroscopy (CRDS) analyzer developed by the National Oceanic and Atmospheric Administration (NOAA). The resulting instrument will be used to measure the optical properties of aerosols aboard Unmanned Aerial Systems (UASs) in highly humidi ...

    SBIR Phase I 2018 Department of CommerceNational Oceanic and Atmospheric Administration
  9. Clean Energy from Air-Sea Temperature Differences

    SBC: SEATREC, INC.            Topic: 8211

    TECHNICAL ABSTRACT: We will demonstrate the feasibility and commercial applicability of a novel energy harvesting system that converts thermal energy from air-sea temperature differences into electricity. This capability will extend the endurance and capability of NOAA observing platforms, reduce lithium battery waste, increase human and environmental safety, and support efforts to detect and moni ...

    SBIR Phase I 2018 Department of CommerceNational Oceanic and Atmospheric Administration
  10. Development of “Permit Wizard” Software for AssistedPermit Application Completion

    SBC: Total Quality Systems, Inc.            Topic: 833

    TECHNICAL ABSTRACT: The objective of this project is to research the technical feasibility of designing a software tool “Permit Wizard” that will automate the process for aquamarine permit application submittal, review, approval/disapproval and issue (including collection of fees). Aquaculture producers are currently faced with slow, complex, and often confusing permitting processes that must ...

    SBIR Phase I 2018 Department of CommerceNational Oceanic and Atmospheric Administration
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