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. 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. 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
  4. 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
  5. Adaptive camera to display mappings using computer vision

    SBC: POLAR RAIN, INC.            Topic: N/A

    The video surveillance industry is experiencing dramatic change with the move from analog to digital video. Command centers need to have coordinated viewing of multiple camera feeds at one time, and the ability to switch automatically between feeds and display relevant patterns. Conventional security control rooms include a bank of monitors connected through a switch to an array of security camera ...

    STTR Phase I 2006 Department of Homeland Security
  6. Information Salience

    SBC: DISCERNING TECHNOLOGIES, LLC            Topic: OSD11TD1

    Empirical-based mathematical framework and computer algorithms, for representing human perception and cognition processes and limitations, which influence the recognition of salient information about rapidly changing events.

    STTR Phase II 2015 Department of DefenseOffice of the Secretary of Defense
  7. Human-Centric Training and Assessment System for Cyber Situational Awareness

    SBC: Scalable Network Technologies, Inc.            Topic: OSD12T08

    The goal of the proposed work is to develop a human-centric training and assessment system for cyber situation awareness. The envisioned system will enable instructors to define training goals, design lesson plans, assign students roles in teams, and observe students performance, record events and interactions for scoring. The instructor/students can place tags (time or event) to roll back or repl ...

    STTR Phase II 2014 Department of DefenseOffice of the Secretary of Defense
US Flag An Official Website of the United States Government