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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. 

This system enables the modular design and optimization of complex plant traits by organizing genes and regulatory mechanisms into interpretable clades.

This invention provides a platform that uses AI agents and biological networks to uncover and interpret disease-relevant biological mechanisms.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.

The need for accurate temperature measurement in critical environments such as nuclear reactors is paramount for safety and efficiency.