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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

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. Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia

    SBC: HVMN Inc.            Topic: SOCOM17C001

    In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  2. 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
  3. Spectrum Analyzer Using Spintronic Radar Arrays

    SBC: Oleandr Scientific LLC            Topic: A16AT016

    We propose to develop a prototype of a novel spintronic spectrum analyzer using an array of nano-scale magnetic spin-torque detectors. The operation of the proposed spectrum analyzer is based on the recently discovered effects of spin-transfer torque and spin-diode effects in nano-scale magnetic multilayered elements, the fabrication of which became possible due to the recent advances in nano-fabr ...

    STTR Phase II 2018 Department of DefenseArmy
  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: Polaris Sensor Technologies, Inc.            Topic: SOCOM18A001

    The objective of this proposal is to develop instrumentation and algorithms for acquiring facial features for facial recognition in low- and no-light conditions.We will use cross-spectrum matching by exploiting infrared polarimetric imagery which tends to show features that match more closely visible imagery than conventional infrared.In addition to thermal infrared, we will also test subjects in ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  6. Technologies to Target Circadian Rhythm Disruption in PTSD

    SBC: Cognionics, Inc.            Topic: A16AT014

    This STTR project will develop a wearable sensor suite for accurate assessment of circadian and sleep rhythms with the goal to identify abnormalities in PTSD patients and enable personalized therapy to help restore their normal functional and quality of life. Phase I has already demonstrated proof-of-principle hardware. The primary Phase II objective is to successfully carry out a human subjects s ...

    STTR Phase II 2018 Department of DefenseArmy
  7. Provably Unclonable Functions on Re-configurable Devices

    SBC: IERUS TECHNOLOGIES, INC            Topic: A18BT001

    The ability to authenticate electronic devices is an important step towards modernizing the hardware/software of our Nations communication systems. Protecting these targeted networks and devices from malicious cyber-based attacks is becoming increasingly important as the technological and cyber capabilities of our adversaries continue to advance. In addition to network security, device authenticat ...

    STTR Phase I 2018 Department of DefenseArmy
  8. Man-Portable and Fieldable Mass Spectrometer for Sequencing Peptides

    SBC: Bayspec, Inc.            Topic: A16AT012

    BaySpec Inc., in collaboration with Pacific Northwest National Laboratory, proposes to develop a new portable multi-order mass spectrometry system that can sequence peptides derived from biological agents including bacteria, viruses, and toxins. During Phase I stage, a fully functional prototype instrument, based on an innovative design concept, was successfully built and the performance evaluatio ...

    STTR Phase II 2018 Department of DefenseArmy
  9. 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
  10. 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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