You are here

Award Data

For best search results, use the search terms first and then apply the filters
Reset

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. IA 2: Intent-Capturing Annotations for Isolation and Assurance

    SBC: Immunant, Inc.            Topic: HR001120S0019001

    Software and hardware flaws can be exploited to make programs perform unintended computations or leak sensitive data. We propose to counter these threats by isolating libraries and other program units inside a single process. The developer will insert source-level annotations that i) map code and data units to compartments and ii) capture how each compartment is intended to interact with others, i ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  3. Sparse Information Orbit Estimation for Proliferated LEO

    SBC: Braxton Technologies, LLC            Topic: HR001119S003522

    Rapidly expanding Low Earth Orbit (LEO) satellite constellations force traditional ground-based tracking methods to adapt as the current ground sensor networks can no longer provide a data rich tracking environment. Accurate tracking information is continually consumed by the Government and private sector to varying degrees of accuracy throughout satellites’ mission lifecycles to provide and uti ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  4. Continuum Actuated Redundant Tendon Robots

    SBC: Opterus Research and Development, Inc.            Topic: HR001119S003523

    Opterus Research and Development, Inc. (Opterus) and Colorado State University (CSU) have combined the best features of high strain composites (HSC), continuum robots, and tendon actuated robots to develop a new concept called Continuum Actuated Redundant Tendon (CART) Robot to enable self-reconfigurable modular robots that can perform various tasks (e.g., walking, crawling, wheeling, and grasping ...

    STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency
  5. Visual Relative Navigation via Intelligent Ephemeral Relationships (VRNIER)

    SBC: TOYON RESEARCH CORPORATION            Topic: ST18C006

    As unmanned aircraft systems (UAS) become more prevalent there is an increasing desire to automate UAS navigation and control. To enable future UASs to perform a wider variety of missions, the they must be able to complete autonomous relative navigation to accomplish missions. Current technologies rely heavily on GPS measurements, which are undesirable since GPS signals may be unavailable in many ...

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
  6. Pathogen Classification Tool (PaCT)

    SBC: Stottler Henke Associates, Inc.            Topic: ST18C002

    Stottler Henke proposes PaCT, leveraging our related past work in computer vision and machine learning. Drawing from techniques used in ExPATSS, a Phase II SBIR effort slated for transition to the Naval fleet, PaCT will perform bacterial characterization using features derived from the phenotype of the bacteria. PaCT will predict bacterial characteristics such as pathogenicity, antibiotic resistan ...

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
  7. Development of Autonomous Glycemic Control Mechanism for Patients Suffering Glycemic Abnormalities as a Result of Critical Illnesses

    SBC: PROFUSA, INC.            Topic: ST18C004

    The use of continuous glucose monitors can be an invaluable management tool for patients afflicted by glycemic variability due to critical illness or trauma. Maintaining stable glucose levels enhances health and lowers care costs, and individuals equipped with continuous glucose data have significantly improved outcomes. Profusa has developed highly miniaturized, injectable, tissue-like, glucose s ...

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
  8. 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
  9. 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
  10. Computational Biology Platform Technology for Cellular Reprogramming

    SBC: IREPROGRAM, LLC            Topic: ST17C001

    Methods for interconversion between cell types (cellular reprogramming) are currently discovered through resource intensive trial and error. Experiments may test a multitude of transcription factors to identify correct combinations that influence cell fate. In addition, reprogramming approaches commonly use stem cell intermediates such as induced pluripotent stem cells (iPSCs), which are generated ...

    STTR Phase I 2018 Department of DefenseDefense Advanced Research Projects Agency
US Flag An Official Website of the United States Government