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Researcher
- Venkatakrishnan Singanallur Vaidyanathan
- Amir K Ziabari
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- Yarom Polsky

ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.

The ever-changing cellular communication landscape makes it difficult to identify, map, and localize commercial and private cellular base stations (PCBS).

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

No readily available public data exists for vehicle class and weight information that covers the entire U.S. highway network. The Travel Monitoring Analysis System, managed by the Federal Highway Administration covers only less than 1% of the US highway network.

This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.

Electrical utility substations are wired with intelligent electronic devices (IEDs), such as protective relays, power meters, and communication switches.

Pairing hybrid neural network modeling techniques with artificial intelligence, or AI, controls has resulted in a unique hybrid system that creates a smart solution for traffic-signal timing.

Current technology for heating, ventilation, and air conditioning (HVAC) and other uses such as vending machines rely on refrigerants that have high global warming potential (GWP).