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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. 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
  2. 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
  3. SeaTag-SP: A Spawning Detecting and Reporting Pop-UpSatellite Tag

    SBC: DESERT STAR SYSTEMS, LLC            Topic: 812

    TECHNICAL ABSTRACT: The application of acoustic sensing in small, affordable, satellite connected ocean devices has broad potential. This proposal focuses at first on the specific topic requirement, designing a popup satellite tag (PSAT) incorporating an acoustic receiver to identify and report the timing and location of fish spawning based on signal presence/absence detection for a tiny pinger wh ...

    SBIR Phase I 2018 Department of CommerceNational Oceanic and Atmospheric Administration
  4. 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
  5. 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
  6. 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
  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. 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
  9. 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
  10. 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

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