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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. Machine Learning Integrated CMOS Terahertz Focal Plane Arrays

    SBC: PRIXARC LLC            Topic: OSD222D02

    Prixarc proposes to develop and commercialize novel terahertz (THz) focal-plane array (FPA) that utilizes 3D microstructures, smart readout integrated circuits, and allows efficient integration with processors that incorporate machine learning to increase the data collection efficiency. We plan to collaborate with University of Miami (UM) and Kansas State University (KSU) for this project. We prop ...

    SBIR Phase II 2023 Department of DefenseNational Geospatial-Intelligence Agency
  2. DIALR Phase II

    SBC: PRIME SOLUTIONS GROUP, INCORPORATED            Topic: OSD221002

    The pace of remotely sensed data collection is increasing exponentially while the skilled workforce that is available to analyze and interpret the data is not. Artificial Intelligence (AI) offers a technology pathway to automation which promises to rapidly reduce the gap between data and information products and services. However, AI techniques require massive quantities of labeled data to train m ...

    SBIR Phase II 2023 Department of DefenseNational Geospatial-Intelligence Agency
  3. 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
  4. GEOGENX: target disambiguation through spatiotemporal context

    SBC: VISION SYSTEMS INC            Topic: NGA201004

    Satellite platforms play a critical role in the modern defense and intelligence infrastructure, providing timely, detailed, and readily available imagery to support U.S. national security. An ever present and fundamental requirement for this type of data is automated target detection and recognition, helping to quickly locate and correctly identify targets from vast quantities of image data. Despi ...

    SBIR Phase II 2023 Department of DefenseNational Geospatial-Intelligence Agency
  5. Graphical Methods for Discovering Structure and Context in Large Datasets

    SBC: MAYACHITRA, INC.            Topic: NGA203005

    In this proposed Phase II effort we will implement a software framework that will reduce the time required to annotate large image/video datasets by a factor of 100x while also reducing the data necessary to train state of the art computer vision models by up to 80%. Our strategy combines several elements and ideas. First, we have developed a sub-tile based a priori theory of how and why CNNs can ...

    SBIR Phase II 2023 Department of DefenseNational Geospatial-Intelligence Agency
  6. HIGH-SPEED ELECTRO-OPTIC SHUTTER

    SBC: TP ENGINEERING SERVICES, LLC            Topic: NGA212001

    In Phase I we developed and demonstrated a bi-directional, monolithic, High-Speed, Electro-optic shutter for Range Gated Imaging. While meeting the majority of the key performance parameters for Range-Gated Imaging at high Pulse Repetition Frequency, improvements can be achieved in transmission, contrast and reliability. The Phase Ii activity begins with a upgraded Electro-optic Shutter incorpora ...

    SBIR Phase II 2023 Department of DefenseNational Geospatial-Intelligence Agency
  7. CHATMAN Phase II

    SBC: Stratagem Group, Inc., The            Topic: OSD221001

    Reducing the False Alarm Rate (FAR) of Automated Target Recognition (ATR) algorithms for Synthetic Aperture Radar (SAR) imagery is crucial for Intelligence, Surveillance, Reconnaissance (ISR) and precision target engagement missions. While modern Deep Learning (DL) ATR networks have demonstrated advanced predictive capabilities and generalization for SAR imagery, they lack spatial awareness, resul ...

    SBIR Phase II 2023 Department of DefenseNational Geospatial-Intelligence Agency
  8. Scene Geometry Aided Automatic Target Recognition (ATR) for Radar

    SBC: Stratagem Group, Inc., The            Topic: OSD221001

    Reducing the false alarm rate (FAR) of Automated Target Recognition (ATR) algorithms is crucial for intelligence, surveillance, reconnaissance (ISR) and precision target engagement missions. There are many contributing factors that result in higher FAR for deep learning (DL) ATR networks operating on Synthetic Aperture Radar (SAR) imagery, including: image distortions, unrepresentative target sign ...

    SBIR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
  9. Geography Aided Inference ATR (GAIA)

    SBC: ETEGENT TECHNOLOGIES, LTD.            Topic: OSD221001

    The amount of data collected from the suite of current and future sensors far surpasses the bandwidth of analysts to processes the data streams into actionable intelligence. This pixel to pupil ratio problem is a forcing function for developing robust algorithms which accurately find non-cooperative objects while minimizing the false alarm rate.  As exploitation algorithms are tasked with perform ...

    SBIR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
  10. Self-Supervised Training in Geospatial Applications with a Robust Hierarchical Vision Transformer (STAR)

    SBC: UNIVERSITY TECHNICAL SERVICES, INC.            Topic: OSD22A001

    Satellite Imagery in Geospatial Intelligence (GEOINT), in conjunction with imagery intelligence (IMINT), geospatial information, and other means of gaining intelligence, has greatly improved the potential of the warfighter and decision makers enabling them to gain a more comprehensive perspective, an in-depth understanding, and a cross-functional awareness of the operational environment. The Artif ...

    STTR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
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