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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. SeaCraft / AeroNautical Data-collector (SCAND) for real-time target recognition

    SBC: HYDRONALIX INC            Topic: SOCOM22DST01

    Intelligent detection and imaging technology hold considerable value for Department of Defense to attain situational awareness and advantage over opposing forces, and for aid in navigating potentially dangerous marine and terrestrial environments. Technologies obtain intelligence on underwater threats and can gather intelligence on approaching surface threats. Current sensor technologies require a ...

    STTR Phase I 2022 Department of DefenseSpecial Operations Command
  2. 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
  3. sUAS Munition Teaming for Advanced Precision Strike

    SBC: CHARLES RIVER ANALYTICS, INC.            Topic: SOCOM21C001

    Precision-guided munitions have demonstrated dramatic effects with minimal collateral damage. New technology developed specifically to deny them accurate guidance information is now feasible, even for non-traditional adversaries. Further, digital communications are flooding the air with signals that interfere with communications many guidance methods rely on. Swarms of small, covert small Uncrewed ...

    STTR Phase I 2022 Department of DefenseSpecial Operations Command
  4. Explainable Query Refinement for Human Machine Teaming

    SBC: KITWARE INC            Topic: SOCOM18B001

    The Intelligence, Surveillance and Reconnaissance (ISR) analysts have a challenging task to extract useful information from huge volumes of data from various sources like Full Motion Video (FMV), Wide Area Motion Imagery (WAMI), satellite imagery, Synthetic Aperture Radar (SAR), and others. Modern Machine Learning (ML) algorithms based on deep learning have greatly advanced computer vision, speech ...

    STTR Phase I 2019 Department of DefenseSpecial Operations Command
  5. System for Nighttime and Low-Light Face Recognition

    SBC: Systems & Technology Research LLC            Topic: SOCOM18A001

    Face recognition performance using deep learning has seen dramatic improvements in recent years. This improvement has been fueled in part by the curation of large labeled training datasets with millions of images of hundreds of thousands of subjects.This results in effective generalization for matching over pose, illumination, expression and age variation, however these datasets have traditionally ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  6. Human Performance Optimization

    SBC: REJUVENATE BIO INC            Topic: SOCOM17C001

    Special Operations Forces (SOF) are an integral aspect of the US military. SOF operators are among the most elite and highly qualified individuals in the U.S. military. As such, extraordinary physical and mental demands are placed upon them to excel in extreme environments for extended periods of time. This unrelenting cycle of combat deployments and intense pre-deployment training shortens the fu ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  7. Incident Surveillance Management System (ISMS)

    SBC: Geospatial Systems, Inc.            Topic: N/A

    Geospatial Systems and Rochester Institute of Technology (RIT) have teamed with Leica Geosystems to develop an Incident Surveillance Management System (ISMS) that can ingest data from remote sensing systems, reduce that data, and deliver information products to decision makers in near real time. The information products are consistent with accepted practice within the NIMS community and utilize st ...

    STTR Phase I 2006 Department of Homeland Security
  8. Innovative 2D/3D Building, Asset, and Resource Tracking Visualization Tool

    SBC: KUTTA TECHNOLOGIES, INC.            Topic: N/A

    In this proposal, Kutta capitalizes on existing DOD investments and its own 2D and 3D visualization tools, and leverages the world-renowned computer graphics department at Arizona State University (ASU). This prior work experience and knowledge allows the team to build a resource and asset tracking tool for incident commanders with powerful 2D and 3D visualization capabilities. Kutta and its prest ...

    STTR Phase I 2006 Department of Homeland Security
  9. Botnet Analytics Appliance (BNA)

    SBC: MILCORD LLC            Topic: N/A

    As reported by Internet security threat reports, Bot networks are becoming the focal point for cybercriminals. Milcord and the University of Wisconsin, responds to this challenge with our proposal ¿ a ¿Bayesian Activity Monitor for Botnet Defense¿ (BAM-BD). In this proposal, we will research, design, and develop a botnet detection and mitigation tool that automatically classifies botnet behavio ...

    STTR Phase I 2006 Department of Homeland Security
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