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Object Recognition and Adaptive Algorithms in Passenger Property Screening

  • Analytical AI (Birmingham, Alabama) will generate deep learning algorithms to develop an object identification engine that can rapidly and accurately detect common stream of commerce items. (Initial award February 2020)—Currently in Phase 4
  • Cignal, LLC (Reedsville, Pennsylvania) will enhance its working prototype and existing training workflow product to generate a high-volume and high-fidelity synthetic Computed Tomography, X-ray, and millimeter wave data sources for labeled Stream of Commerce baggage for seamless, unsupervised, and continuous AI model training. (Initial award May 2020)—Currently in Phase 3
  • Synthetik Applied Technologies (Austin, Texas) will develop and train an artificial intelligence model with the potential to automatically detect multiple objects at the same time during the airport property screening process. (Initial award March 2020)—Completed Phase 4
Last Updated: 01/31/2024
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