Fine-tuning TCAD parameters with real-world feedback from test wafers is essential for quantitatively accurate and predictive results.

Identification of each animal in a collective becomes possible even when individuals are never all visible simultaneously, enabling faster and more accurate analysis of collective behavior.

Investigators developed and validated a masked autoencoder deep learning model using vision transformer technology to automate the detection and grading of nuclear cataracts from slit-lamp images.

Researchers have developed a powerful new artificial intelligence model that can accurately predict biochar yield and composition, helping scientists and industry optimize production while reducing ...

Deep Learning (DL) has emerged as a transformative approach in artificial intelligence, demonstrating remarkable capabilities in solving complex problems once considered unattainable. Its ability to ...

Abstract: Deep learning performs feature extraction through a series of data transformations. Convolutional neural networks (CNNs) are among the most representative methods in deep learning. CNNs ...

An ocean-mining company has funded some of the most comprehensive scientific studies of the deep seabed to date, and peer-reviewed results have begun to emerge. A collage of foraminifera, a kind of ...

During my years teaching science in middle school, high school and college, some of my students have resisted teaching that educators call higher-order thinking. This includes analysis, creative and ...

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...