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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY21 is not expected to be complete until September, 2022.

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. 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
  2. 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
  3. 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
  4. 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
  5. System for Nighttime and Low-Light Face Recognition

    SBC: MUKH Technologies LLC            Topic: SOCOM18A001

    Recognizing faces in low-light and nighttime conditions is a challenging problem due to the noisy and poor quality nature of the images.Thermal imaging is often used to obtain facial biometric in such conditions. Thermal face images, while having a strong signature at nighttime, are not typically maintained in biometric-enabled watch lists and so must be compared with visible-light face images to ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  6. 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
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