You are here

Award Data

For best search results, use the search terms first and then apply the filters
Reset

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. QGAN: Quantum Generative Adversarial Network to Secure Deep Learning

    SBC: INTELLIGENT AUTOMATION, INC.            Topic: SCO183001

    Despite deep neural networks have demonstrated tremendous success in various commercial and DoD applications, they are susceptible to adversarial attacks with detrimental outcomes to the underlying applications. The generative adversarial network (GAN) provides a good way of defending against adversarial learning attacks, but it is faced with a practical challenge, as classical computers are not a ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  2. Critical Program Information (CPI) Identification and Assessment Tool

    SBC: Technology Security Associates, Inc.            Topic: SCO183002

    TSA will assess the feasibility of developing or modifying an existing application-based process for creating: a) A functional architecture of a system to identify system missions, mission threads, and Critical Functions (mission model), and b) A physical architecture of a system (system model) in a manner consistent with both TSN Criticality Analysis and the Cybersecurity Risk Assessment Implemen ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  3. Scalable Low-Cost AESA Transmitter with Phase-Only Nulling

    SBC: Parry Labs, LLC            Topic: SCO182002

    Parry Labs proposes the development and fabrication of a scalable, low-cost, transmit only wideband active electronically scanned array (AESA) operating in Ku band. Operating at Ku band maximizes aperture gain while also minimizing physical size and transmission loss due to rain and other atmospheric effects. The proposed system will be based on a scalable tile building block that can be used to c ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  4. Analog-Digital Hybrid ASIC Implementation of Miniaturized Neural Nets/Portmanteau Industries, LLC

    SBC: Portmanteau Industries, LLC            Topic: SCO182007

    The vision of truly autonomous, smart, and powerful edge devices requires the ability to perform intensive machine learning tasks with limited size, weight, and power budgets. We propose a highly efficient ASIC design that enables edge devices to achieve this vision.

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  5. A High-Throughput and Energy-Efficient Hardware Processor for Vision-based Object Detection Systems/Intelligent Automation, Inc.

    SBC: INTELLIGENT AUTOMATION, INC.            Topic: SCO182007

    We propose to design and implement a high-throughput and energy-efficient FPGA-based hardware processor (accelerator) for the deployment of Convolutional Neural Network (CNN) architectures at real-time embedded and resource-bound environments that have low size, weight, power and cost (SWaP-C) requirements. CNNs have been shown tremendous success in vision-based object detection tasks. Two differe ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  6. REMIX: REconfigurable Machine Intelligence eXtreme compute architecture/Intelligent Computing Machines, LLC

    SBC: Intelligent Computing Machines, LLC            Topic: SCO182007

    We propose the analysis of a proposed architecture called ReMIX: Reconfigurable Machine Intelligence eXtreme compute architecture. This design is a chip multiprocessor with a non-von Neumann architecture and two layers of Network on Chip that enables low-power, high speed, parallel computations with very high throughput. Rather than have data traverse the memory hierarchy as is typical in von Neum ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  7. Deep Reinforcement Learning for Model Training with Simulated Imagery/Next Century Corporation

    SBC: Next Century Corporation            Topic: SCO182006

    Next Century Corporation proposes the development of the Computer Vision Synthetic Image Generation Harness for Training and Testing (CV SIGHTT), a prototype system that learns to train a generation-based image recognition system for low-shot detection in the remote sensing domain. CV SIGHTT will use Deep Evolution Strategies to select the procedure for synthetic image generation, choosing the one ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  8. Deep Automatic Target Recognition (DATR) Technology/R-DEX Systems, Inc.

    SBC: R-DEX Systems, Inc            Topic: SCO182008

    R-DEX Systems proposes to adapt its commercial discrimination technology used in industrial automation to develop Deep Automatic Target Recognition (DATR) Technology. DATR utilizes revolutionary deep learning processing (deep belief networks or DBNs, restricted Boltzmann machines RBMs, and convolutional neural networks or CNNs) to automatically identify hidden, nonlinear features that are not iden ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  9. HLA Development Tools

    SBC: ACUSOFT, INC.            Topic: N/A

    AcuSoft proposes to develop a set of HLA Development Tools to assist simulation software developers in their efforts to implement the HLA. The HLA Development Tools will support the Federation Execution and Development Process (FEDEP) and present an approach to solving the problems associated with the HLA's flexible FOM data definitions. A set of data visualization tools, such as a 2D Plan View ...

    SBIR Phase I 1997 Department of DefenseOffice of the Secretary of Defense
  10. Research and Development of a Synthetic Environment RTI

    SBC: ACUSOFT, INC.            Topic: N/A

    AcuSoft proposes to research and develop a Synthetic Environment RTI (SE-RTI). The SEDRIS initiative has established a new programming paradigm that provides lossless transmission of synthetic environment objects. The HLA has been designed to support interoperability and reuse of DoD simulations, and SEDRIS is a major component of HLA. Currently, the SEDRIS data model, APIs and format are prima ...

    SBIR Phase I 1997 Department of DefenseOffice of the Secretary of Defense
US Flag An Official Website of the United States Government