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ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
Here we present a solution for practically demonstrating path-aware routing and visualizing a self-driving network.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
Electrochemistry synthesis and characterization testing typically occurs manually at a research facility.
A diver-operated system brings safe and portable imaging to a new operating environment – underwater at depths up to 300 feet.
Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.