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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.
How fast is a vehicle traveling? For different reasons, this basic question is of interest to other motorists, insurance companies, law enforcement, traffic planners, and security personnel. Solutions to this measurement problem suffer from a number of constraints.
Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
High strength, oxidation resistant refractory alloys are difficult to fabricate for commercial use in extreme environments.
This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.
In manufacturing parts for industry using traditional molds and dies, about 70 percent to 80 percent of the time it takes to create a part is a result of a relatively slow cooling process.
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).