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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. Generalized Change Detection to Cue Regions of Interest

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA181006

    Toyon proposes to research and develop algorithms for generalized salient change detection, and to incorporate these algorithms into software tools implemented on the cloud. Our approach leverages the two most promising methods from Phase I, both based on supervised learning. The first method is the entropy-based feature vector and corresponding neural network, which we will apply at a coarse sear ...

    SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency
  2. Low-Shot Detection in Remote Sensing Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: NGA172002

    Toyon Research Corporation proposes to develop algorithms that improve the precision and recall of neural networks for low-shot object classification and detection. Our approach is based upon developing a descriptive multi-domain feature representation of the low-shot target as well as the surrounding context. A multi-branch neural network merges the various domains of information to perform accur ...

    SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency
  3. Advanced Image Segmentation for Radar Imagery

    SBC: ELECTROMAGNETIC SYSTEMS, INC.            Topic: NGA172004

    Implement methods to improve our Phase I architecture for complex SAR imagery collected from different systems and with different collection parameters. Implement techniques to boost performance across all ground features of interest. Reduce the amount of human intervention needed for training our SAR image segmentation architecture.  SAR segmentation can be applied to a number of areas: Intellig ...

    SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency
  4. "EXTENDING A HCLPF-BASED SEISMIC MARGIN REVIEW TO ANALYZE PLANT DAMAGE STATES AND THE ROLE OF HUMAN FACTORS AND NON-SEISMIC FAILURES"

    SBC: Future Resources Associate Inc            Topic: N/A

    TECHNIQUES HAVE RECENTLY BEEN DEVELOPED TO ANALYZE THE 'SEISMIC MARGIN' OF A NUCLEAR POWER PLANT USING THE HCLPF CONCEPT (HIGH CONFIDENCE OF A LOW PROBABILITY OF FAILURE). STARTING WITH AN EARTHQUAKE LEVEL SHOSEN FOR MARGIN REVIEW, THE TECHNIQUE DETERMINES WHETHER THE PLANT CAN OR CANNOT 'WITHSTAND THE REVIEW-EARTHQUAKE WITHOUT CORE DAMAGE. HERE 'WITHSTAND' MEANS 'WITHSTAND WITH A HIGH CONFIDENCE ...

    SBIR Phase II 1987 Nuclear Regulatory Commission
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