How meanings align across languages suggests that translation and cross-cultural communication may be challenging, but researchers haven't been clear as to what characterizes this alignment, and what factors might affect ...
A team of chemists and engineers at the University of British Columba working with colleagues at pharmaceutical company Pfizer has developed a chemical processing system combining computer vision with a real-time machine-learning ...
A front-end lens, or meta-imager, created at Vanderbilt University can potentially replace traditional imaging optics in machine-vision applications, producing images at higher speed and using less power.
Magnesium alloys hold promise as a lightweight material to reduce weight in automobiles and transportation systems, offering potential to enhance fuel economy and reduce emissions, but low formability and strength prevent ...
Scientists from the University of Rochester say deep learning can supercharge a technique that is already the gold standard for characterizing new materials. In an npj Computational Materials paper, the interdisciplinary ...
Leaf color patterns, influenced by factors such as leaf age and environmental stress, serve as indicators of plant health in agriculture. The VIS-NIR-SWIR sensor, though effective in measuring these patterns with high resolution, ...
In a review in Nature Reviews Microbiology, Professor Levi Waldron and colleagues highlight the increasing importance of machine learning in microbiology, where it is used for tasks such as predicting antibiotic resistance ...
In a recent study published in Nature Communications, the Vorholt lab investigated the properties of plant microbiota involved in host protection against pathogen colonization. They identified the presence of specific strains ...
Dominik Rothenhaeusler grew up in Oberzell, Germany, a quaint town of roughly 2,500 people along the Schussen River. Like many towns and cities across Germany, Oberzell has witnessed a surge of asylum seekers and refugees ...
Prof. Jiang Bin's research team at the University of Science and Technology of China (USTC) have developed a universal field-induced recursively embedded atom neural network (FIREANN) model, which can accurately simulate ...
