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 FY19 is not expected to be complete until September, 2020.

  1. 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
  2. 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
  3. Manufacturing Data Compiler for Visualization Based on Engineering-Driven Machine Learning

    SBC: OG Technologies, Inc.            Topic: NA

    There has been substantial development in data analytics. However, the complex mathematical formulation of “big data analytics” is difficult to populate in general manufacturing plants. There is a need for an SPC-like tool to enable the acceptance of the advanced data analytics and its visualization. The MD Compiler, a tool to bridge the gap between data available and the information demanded ...

    SBIR Phase I 2018 Department of CommerceNational Institute of Standards and Technology
  4. Secure Role-Based System for Distributed Network Measurement

    SBC: POLLERE, INC.            Topic: NA

    Network measurement is a critical element in networks but it has largely been an afterthought and inadequately secured. With the emergence of Information-Centric Networking technologies, specifically the popular open source Named-Data Networking (NDN), there is the early stage opportunity to create a useful and flexible network measurement system that can accommodate a range of network probes. Thi ...

    SBIR Phase I 2018 Department of CommerceNational Institute of Standards and Technology
  5. Self-Configuring Residential Conditioned Air Zoning System for Low Energy Homes

    SBC: Steven Winter Associates, Inc.            Topic: NA

    Steven Winter Associates, Inc. (SWA) hereby proposes to undertake research to develop a self-configuring residential conditioned air zoning system for low load energy homes. The Phase I prototype will feature zone nodes and a master controller. The zone nodes will measure and wirelessly report environmental conditions to the central controller, and modulate a damper based on commands received from ...

    SBIR Phase I 2018 Department of CommerceNational Institute of Standards and Technology
  6. Dual Plane 3D Compton Scattering Imager with Pixelated CZT Detectors for 1-10MeV Gamma Ray

    SBC: H3D            Topic: NA

    A dual plane Compton imager prototype system with large volume pixelated CZT detectors will be built for spectrally resolved MeV gamma ray tomographic applications. These two planes will be operated at independent clocks and they will be synchronized via a common periodical pulse. The common periodical pulse is self-generated so it does not rely on external pulse generator. Each detector will be c ...

    SBIR Phase I 2018 Department of CommerceNational Institute of Standards and Technology
  7. Compact Raman Fiber Optic Probe with Inline Spectral Filtering

    SBC: Nikira Labs Inc.            Topic: NA

    In this SBIR effort, Nikira Labs Inc. proposes to develop a compact Raman fiber optic probe with inline spectral filtering that improves fiber-coupled Raman measurements by filtering out Raman scattering from the excitation fiber and elastically scattered laser light from the collection fibers. The technology will enable compact fiber probes for Raman studies and complement existing NIST Raman spe ...

    SBIR Phase I 2018 Department of CommerceNational Institute of Standards and Technology
  8. Variational Object Recognition and Grouping Network

    SBC: Intellisense Systems, Inc.            Topic: NGA181005

    To address the National Geospatial-Intelligence Agency (NGA) need for overhead imagery analysis algorithms that provide uncertaintymeasures for object recognition and aggregation, Intellisense Systems, Inc. (ISS) proposes to develop a new Variational Object Recognition andGrouping Network (VORGNet) system. It is based on the innovation of implementing a Bayesian convolutional neural network (CNN) ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  9. 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
  10. 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
US Flag An Official Website of the United States Government