Understanding the neural mechanisms underlying associative threat learning is essential for advancing behavioral models of threat and adaptation. We investigated distinct activation patterns across ...
Abstract: Recently, intelligent fault diagnosis based on deep learning has been extensively investigated, exhibiting state-of-the-art performance. However, the deep learning model is often not truly ...
Abstract: We report a newly developed room-temperature (RT) shimming method for high-temperature superconducting (HTS) magnets employing a deep Q-network (DQN), a type of reinforcement learning theory ...
Porous media are susceptible to fracture. A deep understanding of crack propagation in porous microstructures remains limited to date, owing to the unacceptably expensive cost of numerical modeling ...
MATLAB is a high-performance language and interactive environment used by millions of engineers and scientists worldwide for technical computing, data analysis, algorithm development, and ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
An artificial intelligence (AI) deep learning tool that estimates the malignancy risk of lung nodules achieved high cancer detection rates while significantly reducing false-positive results. Results ...
How do you create 3D datasets to train AI for Robotics without expensive traditional approaches? A team of researchers from NVIDIA released “ViPE: Video Pose Engine for 3D Geometric Perception” ...
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