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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 April, 2020.

  1. 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
  2. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: X-Wave Innovations, Inc.            Topic: DLA18A001

    Additive Manufacturing (AM) is a modern and increasingly popular manufacturing process for metallic components, but suffers from well known problems of inconsistent quality of the finished product. Process monitoring and feedback control are therefore crucial research areas with a goal of solving this problem. To address this concern, X-wave Innovations, Inc. (XII) and the University of Dayton Res ...

    STTR Phase I 2018 Department of DefenseDefense Logistics Agency
  3. 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
  4. Achieving Transformative Productivity through application of Collaborative Augmented Reality Systems (CARS)

    SBC: Vecna Technologies, Inc.            Topic: DLA181001

    The Defense Logistics Agency (DLA) is seeking to automate parts of their procurement, logistics, and distribution processes by applying Augmented Reality (AR) solutions to increase efficiency and reduce costs. Vecna Robotics' world-leading automation consulting team is well-positioned to leverage a deep and broad understanding of advanced technology and its application to warehouse operations. Vec ...

    SBIR Phase I 2018 Department of DefenseDefense Logistics Agency
  5. Additive Manufacturing Process Monitoring and Control Technologies

    SBC: FLIGHTWARE INC            Topic: DLA181002

    The In Process Control for L-PBF (IPCL) program leverages and in process inspection method recently developed and successfully demonstrated for NASA. This Layer Topographic Map or LTM method measures the surface if every melt layer using a commercial laser profilometer. LTM software detects, locates and identifies flawed regions within a layer for every layer in the part. It does so for several co ...

    SBIR Phase I 2018 Department of DefenseDefense Logistics Agency
  6. Low-Shot Detection in Remote Sensing Imagery

    SBC: Next Century Corporation            Topic: NGA172002

    Next Century Corporation proposes the development of Muggsy, a low-shot deep learning detection prototype system that learns to recognize uncommon targets in remote imagery. Our Phase I research extends and leverages an image classification system of our own design called EvoDevo. EvoDevo evolves its own neural network architecture before training to meet the complexity of the data. Muggsy uses le ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  7. GFNet: Gnostic Fields based Low-Shot Learning for Target Detection in Remote Sensing

    SBC: Intelligent Automation, Inc.            Topic: NGA172002

    To detect uncommon targets in remote sensing imagery, it is quite often that very few prior examples are available. This so-called low-shot detection remains a very challenging problem in remote sensing, despite the recent development in state-of-the-art object detection algorithms such as Faster R-CNN and YOLO, and low-shot learning methods such as feature shrinking, model regression and memory a ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  8. DNC-GD: Deep Neural Network Compression for Geospatial Data

    SBC: Intelligent Automation, Inc.            Topic: NGA181009

    Following technology advances in high-performance computation systems and fast growth of data acquisition, a technical breakthroughnamed Deep Learning made remarkable success in many research areas and applications. Nevertheless, the progress of hardwaredevelopment still falls far behind the upscaling of deep neural network (DNN) models at the software level. NGA seeks to apply neuralnetwork minia ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  9. TOFENetTopographic Features Extraction Network

    SBC: Intelligent Automation, Inc.            Topic: NGA181001

    Topographic features found in ground-based natural images contain information that is useful for a variety of applications including locationestimation and navigation. Traditionally these features have been manually labeled by analysts which is costly and time consuming, especiallyconsidering the volume of readily available data. We propose a novel method for extracting topographic features from s ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  10. TopoRobo (Topographical Annotation Robot Software)

    SBC: Next Century Corporation            Topic: NGA181001

    Next Century Corporation proposes to create TopoRobo (topographical annotation robot software) to automatically extract depth-orderedlists of ridge polylines overlaid on an image or video mosaics to feed topography-based geolocation algorithms. TopoRobo will leverage deepneural network machine learning methods optimized for topographical features through EvoDevo, Next Centurys algorithm to grow an ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency

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