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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.

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.

The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.

  1. Enhanced Collaborative Visualization for the Fusion Community

    SBC: Anabas, Inc.            Topic: 53c

    Distributed, collaborative visualization and control of real-time fusion experiments and simulations is of growing importance, because the next major facilities will be internationally located and operated. Currently, collaborative visualization tools for tiled displays in control rooms have substantial overhead and are not satisfactory for tracking dynamic displays. This project will build on m ...

    STTR Phase I 2007 Department of Energy
  2. 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
  3. 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
  4. Cryo-cooled Yb:YAG Lasers for Advanced Photoinjectors

    SBC: Q-PEAK INCORPORATED            Topic: 15d

    Advanced, high brightness photoinjectors are required for the next generation of linear accelerators and free electron lasers. Current photoinjector lasers suffer from complexities related to the use of multiple amplifier stages to achieve the desired pulse energy. There are also issues related to power scaling. This project will investigate the use of a liquid nitrogen cooled, Yb:YAG, mode-loc ...

    STTR Phase I 2007 Department of Energy
  5. 5V, High Gain, High Sensitivity Photomultiplier Detector

    SBC: AGILTRON, INC.            Topic: 26a

    This project will demonstrate a breakthrough detector for the readout of scintillators used for gamma ray detection in Nuclear Physics experiments. The new detector: (1) will overcome the quantum efficiency and high voltage limits of current photomultipliers (PMTs) and Avalanche Photodiodes (APDs); (2) will offer the possibility of improving scintillator detector resolution at least by a factor ...

    STTR Phase I 2007 Department of Energy
  6. SHAPE-BASED GENERALIZATION BOUNDS FOR DEEP LEARNING

    SBC: GEOMETRIC DATA ANALYTICS INC.            Topic: NGA20A001

    We propose to develop a theoretical understanding of the relationship between intrinsic geometric structure in both training and latent data and characteristics of functions learned from that data for deep neural network (DNN) architectures. Along the way we propose to also understand the structure of the neural networks that are best trained on a given data set. Both of these theories will lead t ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  7. NamesforLife Semantic Resolution Services for the Life Sciences (N4L-SRS)

    SBC: NamesforLife, LLC            Topic: 48d

    Within the Genomes-to-Life Roadmap, there is a lack of standardized semantics to accurately describe data objects and persistently express knowledge change over time. As research methods and biological concepts evolve, certainty about the correct interpretation of prior data and published results decreases, because both become overloaded with synonymous and polysemous terms. NamesforLife (N4L) i ...

    STTR Phase I 2007 Department of Energy
  8. Nanoparticle Solar Cell

    SBC: Solexant Corp.            Topic: 10c

    A solution is needed for the inexpensive generation of electricity from solar irradiation, which will be cost competitive with fossil fuel technologies without the need for government subsidies. This project will fabricate and characterize inorganic nanoparticle-based solar cells that: (1) can be manufactured with low cost processing techniques; and (2) will offer greater absorption across the s ...

    STTR Phase I 2007 Department of Energy
  9. Sequestration and Separation of Mercury in Wet Flue Gas Desulfurization Systems

    SBC: ENVERGEX LLC            Topic: 21b

    Mercury regulations passed by the EPA will require stringent mercury emission control from wet flue gas desulfurization scrubbers, used in the production of electricity from coal. The first problem is that a portion of the mercury captured by the wet scrubber is re-emitted. The second problem is that FGD by-products, including gypsum, will increase from 31 million tons in 2004 to 86 million ton ...

    STTR Phase I 2007 Department of Energy
  10. 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
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