1 - 10 of 19 Results
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.
Estimates based on the U.S. Department of Energy (DOE) test procedure for water heaters indicate that the equivalent of 350 billion kWh worth of hot water is discarded annually through drains, and a large portion of this energy is, in fact, recoverable.
The QVis Quantum Device Circuit Optimization Module gives users the ability to map a circuit to a specific quantum devices based on the device specifications.
QVis is a visual analytics tool that helps uncover temporal and multivariate variations in noise properties of quantum devices.
The incorporation of low embodied carbon building materials in the enclosure is increasing the fuel load for fire, increasing the demand for fire/flame retardants.
Modern automobiles are operated by small computers that communicate critical information via a broadcast-based network architecture called controller area network (CAN).
This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.