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Award Data

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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. 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
  3. Biomimetic Slope Adaptive Foot-Ankle Prosthesis

    SBC: MOTION CONTROL, INC            Topic: DHP16C007

    The primary objectiveis to develop acommercially-viable prototype of theslopeadaptive prosthesis design and to iteratively improvethe design based on ISO standards testingand rigorous usein human subject field trials. The proposed work will build upon knowledgegained in PhaseI of the project,which established feasibility for this design approach in alightweight, passive hydraulicfoot-anklesystem. ...

    STTR Phase II 2022 Department of DefenseDefense Health Agency
  4. 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
  5. Bounding generalization risk for Deep Neural Networks

    SBC: Euler Scientific            Topic: NGA20A001

    Deep Convolutional Neural Networks (DCNNs) have become ubiquitous in the analysis of large datasets with geometric symmetries. These datasets are common in medicine, science, intelligence, autonomous driving and industry. While analysis based on DCNNs have proven powerful, uncertainty estimation for such analyses has required sophisticated empirical studies. This has negatively impacted the effect ...

    STTR Phase II 2022 Department of DefenseNational Geospatial-Intelligence Agency
  6. 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
  7. Handoff Training for Combat Casualty Care (HTC3) Framework

    SBC: Perceptronics Solutions, Inc.            Topic: DHA17B001

    This proposal is to develop a Handoff Training for Combat Casualty Care (HTC3) Framework.Training is the crux of the handoff problem today. Patient handoffs are a crucial part of casualty care, both in military and civilian environments; and today handoffs are being performed in less than optimal fashion, with ineffective communications accounting for 80% of the handoff errors. Our new HTC3 Framew ...

    STTR Phase I 2018 Department of DefenseDefense Health Agency
  8. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  9. In-Ear Exposure Sensor with Integrated Noise Attenuation and Communications Capabilities

    SBC: Diversified Technical Systems, Inc.            Topic: DHA20B002

    According to the Department of Defense, there were more than 400,000 known TBI diagnoses in service members between 2000 and 2019 (DVBIC, 2020). Detection and measurement of potential injury due to blast overpressure and blunt impact have been priorities of the US military for many years, especially since Operation Enduring Freedom (OEF). Among those deployed, estimated rates of probable TBI range ...

    STTR Phase I 2021 Department of DefenseDefense Health Agency
  10. In-Mask Sensors for Physiological Investigation of Respiratory Exhalation- INSPIRE

    SBC: MAKEL ENGINEERING, INC.            Topic: DHP16C002

    Makel Engineering, Inc. and Sandia National Laboratories propose to demonstrate an advanced multi-modal sensor system suitable for in-situ analysis of exhaled VOCs for pilots, divers and field patients. Our proposed system will combine a micro-gas chromatograph (GC) and miniature ion mobility spectrometer (IMS) for detection of trace amounts of exhaled breath VOCs with miniature solid state sensor ...

    STTR Phase I 2017 Department of DefenseDefense Health Agency
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