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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. Bounding generalization risk for Deep Neural Networks

    SBC: Euler Scientific            Topic: NGA20A001

    Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  2. Algorithms for Look-down Infrared Target Exploitation

    SBC: SIGNATURE RESEARCH, INC.            Topic: NGA18A001

    The multidisciplinary area of GEOINT is changing and becoming more complex. A major driver of innovation in GEOINT collection and processing is artificial intelligence (AI). AI is being leveraged to help accomplish spatial analysis, change detection, and image or video triage tasks where filtering objects of interest from large volumes of data is critical. NGA is confronting the changing GEOINT l ...

    STTR Phase II 2020 Department of DefenseNational Geospatial-Intelligence Agency
  3. Human Performance Optimization

    SBC: HVMN Inc.            Topic: SOCOM17C001

    During altitude-induced hypoxia, operator cognitive and physical capacity degrades, compromising individual and team performance. Cognitive degradation is linked to falling brain energy levels, increased reliance on anaerobic energy production and lactate accumulation. Ketones are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies demonstrated that ...

    STTR Phase II 2019 Department of DefenseSpecial Operations Command
  4. Human Performance Optimization

    SBC: REJUVENATE BIO INC            Topic: SOCOM17C001

    Special OperationsForces (SOF)are an integral aspect of the US military. SOF operators are among the most elite and highly qualified individuals in the U.S.military. As such, extraordinary physical and mental demands are placed upon them to excel in extreme environments for extended periods of time. This unrelenting cycle of combat deployments and intense pre-deployment training shortens the funct ...

    STTR Phase II 2019 Department of DefenseSpecial Operations Command
  5. 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
  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. Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia

    SBC: HVMN Inc.            Topic: SOCOM17C001

    In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  8. Retrofittable and Transparent Super-Insulator for Single-Pane Windows

    SBC: NANOSD, INC.            Topic: DEFOA0001429

    NanoSD, Inc. with its partners will develop a transparent, nanostructured thermally insulating film that can be applied to existing single-pane windows to reduce heat loss. To produce the nanostructured film, the team will create hollow ceramic or polymer nanobubbles and consolidate them into a dense lattice structure using heat and compression. Because it is mostly air, the resulting nanobubble s ...

    STTR Phase II 2016 Department of EnergyARPA-E
  9. Development of Advanced Military Prosthetic Shoulder System

    SBC: Sarcos Group LC            Topic: A05161

    A new dual pump hydraulic supply designed to enable energetically autonomous exoskeleton robots will be developed, tested and demonstrated. This new hydraulic supply will be integrated with a high performance hydraulically actuated full body exoskeleton robot and used to test and demonstrate the overall performances of such systems. New control policies that include: (i) an assist mode, where the ...

    STTR Phase II 2017 Department of DefenseSpecial Operations Command
  10. Data Driven Intent Recognition Framework

    SBC: Other Lab Inc.            Topic: NSF13599

    A critical aspect of exoskeleton control that has to date introduced a performance limitation is the ability of the exoskeleton to recognize the intent of the operator so it can apply assistance to their desired motion. This intent recognition effort is typically solved using ad-hoc methods where subject matter experts make design decisions and tune transitions to identify intended maneuvers as re ...

    STTR Phase II 2016 Department of DefenseSpecial Operations Command
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