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INTELLIGENT FUSION TECHNOLOGY, INC.

Company Information
Address
20271 Goldenrod Ln Ste 2066
Germantown, MD 20876-4104
United States


http://www.i-fusion-i.com/

Information

DUNS: 967349668

# of Employees: 21


Ownership Information

HUBZone Owned: No

Socially and Economically Disadvantaged: Yes

Woman Owned: Yes



Award Charts




Award Listing

  1. Information-Centric Networking for Intelligent Cooperative Perception of Air Vehicles

    Amount: $149,982.00

    In this project, we propose to develop a distributed deep reinforcement learning-based intelligent cooperative perception system (iCOOPER) with information-centric networking, which enables autonomous ...

    STTRPhase I2021Department of Defense Air Force
  2. (3) Condition-Based Predictive Maintenance for Mission Critical Systems with Probabilistic Knowledge Graph and Deep Learning

    Amount: $150,000.00

    New tools and technologies are needed for modern US Navy surface and aviation fleets to augment current onboard condition monitoring and maintenance processes and help improve mission-critical systems ...

    SBIRPhase I2020Department of Defense Navy
  3. Adaptive Signal Analysis System for Non-periodic Signals

    Amount: $140,000.00

    This proposal aims to develop advanced signal analysis tools for utilization on non-periodic radio frequency signal sources that have the capability to detect, process, generate and classify non-perio ...

    SBIRPhase I2020Department of Defense Navy
  4. Real-time Trend and Sentiment Analysis and Tracking with Dynamic Knowledge Graph

    Amount: $140,000.00

    This effort proposes to develop a real-time KG-based Trend and Sentiment Analysis (KG-TSA) system with dynamic Knowledge Graph. KG-TSA provides a solution for intelligence analysis where no obvious mo ...

    SBIRPhase I2020Department of Defense Navy
  5. Distributed Cooperative Beamforming Oriented High-Precision Time and Phase Synchronization of RF Sources across Multiple UAS Platforms a Dynamic and G

    Amount: $139,996.00

    To obtain high-precision time and phase synchronization (phase coherency) of multiple distributed radio frequency (RF) sources located on Unmanned Aerial Systems (UAS’s) platforms, we propose a holi ...

    SBIRPhase I2020Department of Defense Navy
  6. CARES: Cloud-based Aircraft Readiness Enhancement and Sustainment with Digital Twins

    Amount: $139,994.00

    For aviation systems, digital twin (DT) technology has a potential to improve supply chain integrity, flight safety, in-flight service, foreign object detection, and condition-based maintenance. It he ...

    SBIRPhase I2020Department of Defense Navy
  7. CRISIS: Knowledge Graph Based Cyber Resilience Integrated Security Inspection System

    Amount: $140,000.00

    Modern US Navy ships and submarines are configured with an ever-increasing level of automation, including state-of-the-art embedded wireless sensors that monitor vital system functions. However, senso ...

    STTRPhase I2020Department of Defense Navy
  8. A Metadata Management and Visualization System for Radio Frequency Activity Modeling and Pattern Recognition

    Amount: $749,999.00

    In current Naval Communications Intelligence operations, significant volumes of potentially valuable, “non-analyzable”, intercepted data are discarded. By using an Automated Radio Frequency Activi ...

    SBIRPhase II2020Department of Defense Navy
  9. (3) Condition-Based Predictive Maintenance for Mission Critical Systems with Probabilistic Knowledge Graph and Deep Learning

    Amount: $1,599,972.00

    Introducing the I-SEER, Intelligent Fusion Technology’s - SErvice Enhanced Recommender, a data analysis web application for condition-based predictive maintenance (CBPM). CBPM provides insight into ...

    SBIRPhase II2020Department of Defense Navy
  10. Machine Learning based Domain Adaptation (MLB-DA) for Multiple Source Classification and Fusion

    Amount: $150,000.00

    Generalizing models learned on one domain to novel domains has been a major obstacle in the quest for universe object recognition. The performance of the learned models degrades significantly when tes ...

    STTRPhase I2020Department of Defense Air Force
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