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Award Data
The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.
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.
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Scalable Low-Cost AESA Transmitter with Phase-Only Nulling
SBC: PARRY LABS, LLC Topic: SCO182002Parry 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 -
Deep Reinforcement Learning for Model Training with Simulated Imagery/Next Century Corporation
SBC: Next Century Corporation Topic: SCO182006Next 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 -
Analog-Digital Hybrid ASIC Implementation of Miniaturized Neural Nets/Portmanteau Industries, LLC
SBC: Portmanteau Industries, LLC Topic: SCO182007The 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 -
A High-Throughput and Energy-Efficient Hardware Processor for Vision-based Object Detection Systems/Intelligent Automation, Inc.
SBC: Intelligent Automation, Inc. Topic: SCO182007We 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 -
REMIX: REconfigurable Machine Intelligence eXtreme compute architecture/Intelligent Computing Machines, LLC
SBC: INTELLIGENT COMPUTING MACHINES LLC Topic: SCO182007We 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 -
QGAN: Quantum Generative Adversarial Network to Secure Deep Learning
SBC: Intelligent Automation, Inc. Topic: SCO183001Despite 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 -
Critical Program Information (CPI) Identification and Assessment Tool
SBC: Technology Security Associates, Inc. Topic: SCO183002TSA 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