1 - 10 of 14 Results
ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
The eDICEML digital twin is proposed which emulates networks and hosts of an instrument-computing ecosystem. It runs natively on an ecosystem’s host or as a portable virtual machine.
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.
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.
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.
Electrochemistry synthesis and characterization testing typically occurs manually at a research facility.
This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.