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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.

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. 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. 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
  3. 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
  4. 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
  5. 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
  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
  7. Near Atomic Spatial Resolution Electrical Characterization

    SBC: SPM Labs LLC            Topic: DMEA19B001

    The proposal “Down to Atomic Resolution Kelvin Probing of Integrated Circuits (DARK-PICs)” deals with improvement of Kelvin Force Microscopy (KFM) allowing detection/mapping of surface potential and related electric properties of semiconductors and integrated circuits at the atomic scale. This Phase I deals with the feasibility of developing a commercially KFM system with a spatial resolution ...

    STTR Phase I 2020 Department of DefenseDefense Microelectronics Activity
  8. Advanced Predictive Modeling of Radiation Effects in ReRAM Devices based on electrical characterization augmented by imaging data

    SBC: Desert Microtechnology Associates, Inc.            Topic: 20A001

    In an effort to improve the design of radiation hardened electronic components, this proposal explores the feasibility of creating predictive modeling techniques for nanoscale material properties in advanced integrated electrical devices. This study encompasses the collaborative usage of high resolution Transmission Electron Microscope (HR-TEM) data, circuit design targeted electrical data, and ma ...

    STTR Phase I 2020 Department of DefenseDefense Microelectronics Activity
  9. Investigation of Radiation Effects in Advanced Microelectronic Devices for developing predictive models of degradation

    SBC: CFD RESEARCH CORPORATION            Topic: 20A001

    Radiation effects in microelectronic components are a significant concern for the reliability of DoD systems that operate at high altitudes or in outer space. Typical characterization efforts focus on macroscale degradation signatures from electrical measurements at device terminals. However, a comprehensive analysis of radiation-induced physical defects is not possible based solely on terminal me ...

    STTR Phase I 2020 Department of DefenseDefense Microelectronics Activity
  10. Predictive device modeling for radiation effects through machine learning

    SBC: ALPHACORE INC            Topic: 20A001

    Alphacore will evaluate and develop a new approach to multi-scale modeling of radiation effects in electronic device technologies based on novel material systems. Our approach aims to directly correlate nano-scale properties of novel materials systems with macro-scale electrical properties of devices constructed with those materials, and their radiation response. Radiation hardness assurance (RHA) ...

    STTR Phase I 2020 Department of DefenseDefense Microelectronics Activity
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