Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine ...

Particle physics may have been an early adopter, but AI has now spread throughout physics. This shouldn’t be too surprising. Physics is data-heavy and computationally intensive, so it benefits from ...

“ORNL is leading the AI frontier in science,” Potok concluded. “We are using AI to simulate, predict and accelerate ...

For robots to be successfully introduced in a wider range of real-world settings, they should be able to safely and reliably ...

Automated Model Generation (AMG) algorithms are an important technique for creating Artificial Neural Network (ANN) models in microwave design automation. AMG integrates all the subtasks in ANN ...

Decision-making often involves trial and error, but conventional models assume we always act optimally based on past experience.

When solving decision-making problems with mathematical optimization, some constraints or objectives may lack analytic expressions but can be approximated from the data. When an approximation is made ...

Delaware-based TheStage AI is changing this paradigm with their innovative approach to neural network optimization. The startup recently announced a $4.5 million funding round to commercialize ...

Convolutional neural networks, deep learning, fracture, skull. Each article is made available under the terms of the Creative Commons Attribution-Non Commercial 4.0 License.

Here we report an ultrafast (0.4 s) hydrogen detection system based on a wafer-scale fabrication process. It consists of a low power (20.2 mW) hydrogen sensor based on vertical thermal conduction ...