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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. 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
  2. SHAPE-BASED GENERALIZATION BOUNDS FOR DEEP LEARNING

    SBC: GEOMETRIC DATA ANALYTICS            Topic: NGA20A001

    We propose to develop a theoretical understanding of the relationship between intrinsic geometric structure in both training and latent data and characteristics of functions learned from that data for deep neural network (DNN) architectures. Along the way we propose to also understand the structure of the neural networks that are best trained on a given data set. Both of these theories will lead t ...

    STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  3. Method for Locally Measuring Strength of a Polymer-Inorganic Interface During Cure and Aging

    SBC: METNA CO            Topic: A17AT016

    A nondestructive test system is under development for thorough, rapid and economical evaluation of the structure and properties of polymer-inorganic interfaces during curing and in service. The system is capable of in-situ, real-time and spatially resolved monitoring of the molecular structure and properties. It employs (single-sided) NMR relaxometry principles to detect and quantify defects and d ...

    STTR Phase II 2020 Department of DefenseArmy
  4. Vibration-Enhanced Sensing of Buried Landmines

    SBC: Vadum, Inc.            Topic: A16AT004

    Vadum proposes to mature its Vibration-Enhanced Underground Sensing (VENUS) technology into a reliable, shallow-buried low-metal-content landmine discrimination and classification solution with minimal False Alarm Rate (FAR).  VENUS exploits a novel vibration phenomenology to provide unique discriminatory information and estimated classification of the buried target that enhances and complements ...

    STTR Phase II 2020 Department of DefenseArmy
  5. Algorithms for Look-down Infrared Target Exploitation

    SBC: Signature Research, Inc.            Topic: NGA18A001

    The multidisciplinary area of GEOINT is changing and becoming more complex. A major driver of innovation in GEOINT collection and processing is artificial intelligence (AI). AI is being leveraged to help accomplish spatial analysis, change detection, and image or video triage tasks where filtering objects of interest from large volumes of data is critical. NGA is confronting the changing GEOINT l ...

    STTR Phase II 2020 Department of DefenseNational Geospatial-Intelligence Agency
  6. Radio Disruption of Electronic Systems

    SBC: Vadum, Inc.            Topic: A19CT007

    Vadum and North Carolina State University will develop Radio Disruption of Electronic Systems (RADES) to deliver standoff denial of swarming adversary unmanned aircraft systems (UAS). Novel RADES waveforms bypass common jamming mitigation techniques by exploiting a widened attack surface of fundamental electronic hardware vulnerabilities in UAS. Integrated with a software-defined radio (SDR) on a ...

    STTR Phase I 2020 Department of DefenseArmy
  7. Mm-Wave Phased-Array Antennas with Ultra-Low-Latency Beam-Forming and Spatial-Filtering for Highly Dynamic and Mobile Satellite Communications

    SBC: Alcatera Inc.            Topic: A19CT006

    This project aims to reduce the size and cost of current AEHF front-end by the integration of a compact beam-steering antenna array. The integration consists of novel antenna design, novel steering technique, and a scalable capable architecture.

    STTR Phase I 2020 Department of DefenseArmy
  8. Freeform Optics for Small Arms Fire Control

    SBC: SA Photonics, Inc.            Topic: A19BT001

    Traditional spherical optics implemented on a common optical axis are the foundation of today’s fielded gunsights for small arms fire control. SA Photonics has helped pioneer the application of precision injection molded freeform optical surfaces in head/helmet mounted display (HMD) systems for augmented reality (AR), virtual reality (VR) and low light level sensor applications. SA Photonics tea ...

    STTR Phase I 2020 Department of DefenseArmy
  9. ConnextEdge: A Hierarchical Framework for Resilient Edge Analytics

    SBC: Real-time Innovations, Inc.            Topic: A19CT004

    The US Army aims to integrate multi-modal sensor data streams and advanced AI analytics at the tactical network edge in support of its vision for a future Internet of Battlefield Things. To maintain situational awareness within mission-acceptable levels despite dynamic conditions and infrastructure disruptions, we propose the ConnextEdge framework for resource-aware location-agnostic adaptive AI p ...

    STTR Phase I 2020 Department of DefenseArmy
  10. Tactical Edge Sensor Processing- Edge Learning System Orchestration and Management

    SBC: HIKINO ASSOCIATES, LLC            Topic: A19CT004

    Intelesense Technologies (rebranding as IoT/AI), in partnership with Southwest Research Institute (SwRI), proposes to demonstrate an Edge Learning System Orchestration and Management system. The system is distributed and hierarchical adaptation and learning system design through emulations and simulation based on IoT/AI’s work in distributed intelligence “edge as a service” systems that aggr ...

    STTR Phase I 2020 Department of DefenseArmy
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