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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. Adaptive camera to display mappings using computer vision

    SBC: POLAR RAIN, INC.            Topic: N/A

    The video surveillance industry is experiencing dramatic change with the move from analog to digital video. Command centers need to have coordinated viewing of multiple camera feeds at one time, and the ability to switch automatically between feeds and display relevant patterns. Conventional security control rooms include a bank of monitors connected through a switch to an array of security camera ...

    STTR Phase I 2006 Department of Homeland Security
  2. AI/ML Aided Aviation Sensors for Cognitive and Decision Optimization

    SBC: KRTKL INC.            Topic: SOCOM23B001

    krtkl (“critical”) will conduct a Phase I Feasibility Study to identify the best approach for reducing aviator cognitive load by optimizing information delivery and decision-making based on a thorough analysis of existing platforms, sensors, data sources, and onboard compute resources. This information will be used to identify Artificial Intelligence and Machine Learning based algorithms for p ...

    STTR Phase I 2023 Department of DefenseSpecial Operations Command
  3. Algorithm Performance Evaluation with Low Sample Size

    SBC: SIGNATURE RESEARCH, INC.            Topic: NGA20C001

    The team of Signature Research, Inc. and Michigan Technological University will develop and demonstrate methods and metrics to evaluate the performance of machine learning-based computer vision algorithms with low numbers of samples of labeled EO imagery. We will use the existing xView panchromatic dataset to demonstrate a proof-of-concept set of tools. If successful, in Phase II, we will extend t ...

    STTR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency
  4. 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
  5. Biomimetic Slope Adaptive Foot-Ankle Prosthesis

    SBC: MOTION CONTROL, INC            Topic: DHP16C007

    Biomimetic Slope Adaptive Foot-Ankle Prosthesis This project will develop an innovative mechanical/hydraulic foot-ankle system that will help lower extremity prosthesis wearers to walk or run in a wider range of environments with close to normal walking biomechanics. The proposed system will have a unique combination of features, all mechanically implemented without electronics or external powe ...

    STTR Phase I 2017 Department of DefenseDefense Health Agency
  6. Bounding generalization risk for Deep Neural Networks

    SBC: Euler Scientific            Topic: NGA20A001

    Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  7. CCHAT Handoff Protocol

    SBC: SOAR TECHNOLOGY INC            Topic: DHA17B002

    Research has identified that handoffs are particularly important communication processes, during which communication error can lead to patient safety situations. Organizations have created standard practices and training materials to encourage teamwork communication for handoffs, however these do not necessarily capture the needs of military medicine of combat casualty care. Combat casualty handof ...

    STTR Phase I 2018 Department of DefenseDefense Health Agency
  8. Combat Casualty Handoff Automated Trainer (CCHAT)

    SBC: SOAR TECHNOLOGY INC            Topic: DHA17B001

    Combat casualty handoffs are critical communication moments during which responsibility for the patient and important casualty information is transferred between providers. The nature of these handoffs requires specialized training, for which no standardized framework currently exists. The proposed effort aims to develop a capability, compatible with current DoD systems, that provides caregivers w ...

    STTR Phase I 2018 Department of DefenseDefense Health Agency
  9. Comfortable, Easy-To-Fit, Deep-Insert Earplug

    SBC: PAXAURIS LLC            Topic: DHA19C001

    Effective hearing protection is essential for service members who work in hazardous noise environments and for whom permanent or even temporary hearing damage affects performance, endangers lives, and reduces quality of life. Various devices have been developed to attenuate high levels of impulse and continuous noise while allowing low-level sounds to pass through. However, issues with comfort, ea ...

    STTR Phase I 2020 Department of DefenseDefense Health Agency
  10. CORE-Military: A Virtual Reality Platform for Emergency Care Training and Assessment in Austere Environments

    SBC: Radiant Images Inc.            Topic: DHA20B001

    In emergency medicine, time is a critical factor that can significantly influence the survival of seriously ill patients. Early recognition of clinical deterioration and rapid initial management is paramount in any setting where emergency care is provided. In military medicine and humanitarian care, delivering high quality and timely care to injured patients poses even greater and more complex cha ...

    STTR Phase I 2021 Department of DefenseDefense Health Agency
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