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The Award database is continually updated throughout the year. As a result, data for FY19 is not expected to be complete until April, 2020.

  1. Developing Commercial Quantum Resistance Standard Based on Epitaxial Graphene

    SBC: Graphene Waves, LLC            Topic: None

    Graphene Waves proposes to develop a quantum Hall resistance (QHR) standard based on graphene that can be deployed for general electrical calibration in industries. Current QHR standard is based on GaAs/AlGaAs heterostructure and requires expensive liquid helium to operate. The continuous increase in price and unstable supply chain of liquid helium limit the QHR standard to be only affordable by t ...

    SBIR Phase I 2019 Department of CommerceNational Institute of Standards and Technology
  2. Laser Particle Separation

    SBC: Opthos Instrument Company, LLC            Topic: None

    Parman Tech is dedicated to commercializing a NIST technology for sorting nano-particles. This technology uses the force of light to gently guide particles along different paths depending on the size of makeup of each particle.

    SBIR Phase I 2019 Department of CommerceNational Institute of Standards and Technology
  3. TheSieve

    SBC: Cyber Point International, LLC            Topic: None

    CyberPoint International presents the design of a cross platform product for the autonomous execution of live forensic investigations of Personal Computers, Laptops and Servers leveraging the NIST NSRL corpus and a combination of at least 3 forms of machine learning/artificial intelligent algorithms for the processing of preliminary digital evidence titled TheSieve. We build upon work from our pha ...

    SBIR Phase II 2019 Department of CommerceNational Institute of Standards and Technology
  4. TheSieve

    SBC: Cyber Point International, LLC            Topic: NA

    We propose to create an advanced forensic analysis tool called TheSieve. This tool will use machine learning techniques that can classify files as malicious or benign as well as suggesting files for closer inspection. Built upon custom enhancements to the National Software Reference Library (NSRL), TheSieve will allow forensic investigators to spend theirvaluable time examining the most significan ...

    SBIR Phase I 2018 Department of CommerceNational Institute of Standards and Technology
  5. Development of a Rapid Monitoring System for Detection of Pathogens in Marine Aquaculture Operations

    SBC: InnovaPrep, LLC            Topic: 836

    TECHNICAL ABSTRACT: InnovaPrep proposes to develop a rapid sample-to-answer monitoring system for detecting pathogens in marine aquaculture waters. An assessment of industry needs will include a kickoff meeting with NOAA and a visit to Toby Island Bay Oyster Farm. Following the assessment and report, a TRL-4 breadboard prototype system will be developed that will include the combination of sample ...

    SBIR Phase I 2018 Department of CommerceNational Oceanic and Atmospheric Administration
  6. Deep Sea Vision AI: Deep Learning-Based Real-Time Marine Animal Detection for Entanglement Mitigation

    SBC: Synthetik Applied Technologies LLC            Topic: 832

    TECHNICAL ABSTRACT: The objective of this project is to develop and implement a real-time detection and warning system to mitigate marine entanglement events in offshore aquaculture operations. In order to achieve this, we leverage the latest advances in computer vision, deep learning, and real-time object detection to develop a real-time marine life detection, classification and tracking pipeline ...

    SBIR Phase I 2018 Department of CommerceNational Oceanic and Atmospheric Administration
  7. Low-Shot Detection in Remote Sensing Imagery

    SBC: Next Century Corporation            Topic: NGA172002

    Next Century Corporation proposes the development of Muggsy, a low-shot deep learning detection prototype system that learns to recognize uncommon targets in remote imagery. Our Phase I research extends and leverages an image classification system of our own design called EvoDevo. EvoDevo evolves its own neural network architecture before training to meet the complexity of the data. Muggsy uses le ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  8. GFNet: Gnostic Fields based Low-Shot Learning for Target Detection in Remote Sensing

    SBC: Intelligent Automation, Inc.            Topic: NGA172002

    To detect uncommon targets in remote sensing imagery, it is quite often that very few prior examples are available. This so-called low-shot detection remains a very challenging problem in remote sensing, despite the recent development in state-of-the-art object detection algorithms such as Faster R-CNN and YOLO, and low-shot learning methods such as feature shrinking, model regression and memory a ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  9. DNC-GD: Deep Neural Network Compression for Geospatial Data

    SBC: Intelligent Automation, Inc.            Topic: NGA181009

    Following technology advances in high-performance computation systems and fast growth of data acquisition, a technical breakthroughnamed Deep Learning made remarkable success in many research areas and applications. Nevertheless, the progress of hardwaredevelopment still falls far behind the upscaling of deep neural network (DNN) models at the software level. NGA seeks to apply neuralnetwork minia ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  10. TOFENetTopographic Features Extraction Network

    SBC: Intelligent Automation, Inc.            Topic: NGA181001

    Topographic features found in ground-based natural images contain information that is useful for a variety of applications including locationestimation and navigation. Traditionally these features have been manually labeled by analysts which is costly and time consuming, especiallyconsidering the volume of readily available data. We propose a novel method for extracting topographic features from s ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency

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