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The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.

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. Printable Dielectric for Flexible Hybrid Electronics

    SBC: ChemCubed, LLC            Topic: 2

    The goal for this Phase I research is to develop a stretchable dielectric ink that can be used for flexible applications. Printing electronics is a new and quickly growing alternative to traditionally manufactured electronics. Flexible hybrid electronics (FHE) is a novel approach to electronic circuit manufacturing that aims to combine the best of printed and conventional electronics. FHE devices ...

    SBIR Phase I 2023 Department of CommerceNational Institute of Standards and Technology
  2. Multi-Task Scale-aware Continuous and Localizable Embeddings

    SBC: KITWARE INC            Topic: OSD22A001

    In Phase I, our team of Kitware and UC-Berkeley developed Scale-MAE by adding ground sample distance (GSD) to positional encodings, and produced a multiscale representation that achieves state-of-the art results across image classification, semantic segmentation, and object detection tasks. In Phase II, we will create a remote sensing pretraining toolkit to enable fast and easy experimentation wit ...

    STTR Phase II 2023 Department of DefenseNational Geospatial-Intelligence Agency
  3. Artificial Intelligence (AI) based algorithms for predictive maintenance using NOAA data-sets for renewable energy assets

    SBC: 60Hertz Incorporated            Topic: 92

    This research aims to develop decision support tools for better maintenance and planning of renewable energy generation and storage assets using atmospheric, local weather, and on-ground environmental data blended with site-, regional- and national-generation data. The study will use a combination of these data to understand the relationship between non-cloud cover based atmospheric conditions and ...

    SBIR Phase II 2023 Department of CommerceNational Oceanic and Atmospheric Administration
  4. MONET: Modeling non-Objects and Novelty for Efficient Training

    SBC: KITWARE INC            Topic: OSD221003

    Object detection datasets for overhead imagery are typically generated using bootstrapping methods to reduce annotator effort and cost. These methods iteratively train a detector from a limited set of user-provided and model-predicted labels. Such approaches bias detectors toward the initial object set, limiting their capacity to handle object variations or discover novel objects classes. MONET ov ...

    SBIR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
  5. Nanocomposite Dielectric Material and Printing Process for Energy Efficient Manufacturing of Printed Circuitry

    SBC: ChemCubed, LLC            Topic: 2

    There is tremendous potential to manufacture printed electronics in a more sustainable, flexible, faster, and less costly way. However, innovations in materials have been required for full scale manufacturing. In their successful Phase I, ChemCubed (C3) developed a nanocomposite dielectric with electrical and thermal properties similar to those of FR4 boards currently used in PCB manufacturing. In ...

    SBIR Phase II 2022 Department of CommerceNational Institute of Standards and Technology
  6. Nano-Electro-Mechanical-Systems Probe for Thin Film Materials Characterization

    SBC: Xallent LLC            Topic: 2

    The ability to quickly test materials during new technology development would provide actionable insight that would significantly reduce materials and device design iterations and accelerate time-to-market. However, conventional characterization and test methods are increasingly ineffective when applied to structures less than 100 nanometers, causing challenges across R&D, process control, and fai ...

    SBIR Phase II 2022 Department of CommerceNational Institute of Standards and Technology
  7. Artificial Intelligence (AI) based algorithms for predictive maintenance using NOAA data-sets for renewable energy assets

    SBC: 60Hertz Incorporated            Topic: 92

    We propose to use Aerosol Optical Depth (AOD) measurements as an early warning system, to cue on-site validation of the soiling station and any available meteorological (MET) station data to validate if a work order to clean deposited particulate matter is necessary. This would move from reactive maintenance – often weeks delayed, to proactive maintenance – getting ahead of the weather impact ...

    SBIR Phase I 2022 Department of CommerceNational Oceanic and Atmospheric Administration
  8. Multi-Task Scale Aware Continuous and Localizable Embeddings

    SBC: KITWARE INC            Topic: OSD22A001

    NGA uses deep networks for many tasks including image registration, land cover segmentation, and object detection. Current deep learning approaches develop specialist networks for each task and type of data. Not only is this inefficient, because networks can’t be reused across tasks, this approach ignores correlations between tasks and data sources that can improve performance. In response, we w ...

    STTR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
  9. Region Reduction

    SBC: CLARIFAI, INC.            Topic: NGA201006

    The NGA program “GLIMPSE” leverages context and topography to geolocate imagery for further analysis. For this proposal, Clarifai intends to develop and deliver a deep-learning pipeline to reduce the geographical search space for an image that will expedite analysis and reduce computational cost. The objective of this proposal is to provide a system to (a) efficiently identify relevant imagery ...

    SBIR Phase II 2022 Department of DefenseNational Geospatial-Intelligence Agency
  10. Clarifai Response to Topic Number: NGA 201-001 Phase II Rare Objects

    SBC: CLARIFAI, INC.            Topic: NGA201001

    Computer Vision AI models are trained on large datasets to understand imagery and assist with human analysis in thousands of use cases. This proposal is intended to enable the use of machine-learned computer vision to assist analysts in the location of rare objects even when there is insufficient real world labeled data for deep training. The generic problem of automatic recognition of objects fro ...

    SBIR Phase II 2021 Department of DefenseNational Geospatial-Intelligence Agency
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