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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.

Download all SBIR.gov award data either with award abstracts (290MB) or without award abstracts (65MB). A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.

  1. High Power Density Dual Rotor Permanent Magnet Motor with Integrated Cooling and Drive for Aircraft Propulsion

    SBC: Advanced Magnet Lab, Inc.            Topic: 1

    There is a critical need for electrification of transportation systems. The proposed technology enables the development of very high-power density permanent magnet motors, which when coupled to an integrated SiC drive allows for an overall specific power beyond 12 kW/kg. The proposed concept relies on the tight integration of a high-power density dual-rotor permanent magnet motor, high power densi ...

    STTR Phase I 2020 Department of EnergyARPA-E
  2. 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
  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. Vertical GaN Substrates

    SBC: Sixpoint Materials, Inc.            Topic: N/A

    SixPoint Materials will create low-cost, high-quality vertical gallium nitride (GaN) substrates using a multi-phase production approach that employs both hydride vapor phase epitaxy (HVPE) technology and ammonothermal growth techniques to lower costs and maintain crystal quality. Substrates are thin wafers of semiconducting material needed for power devices. In its two-phase project, SixPoint Mate ...

    STTR Phase I 2014 Department of EnergyARPA-E
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