MIT researchers say they have found a more efficient way to train machine learning models that predict how complex metal alloys will behave.
UTokyo and Kubota develop a drone potato yield prediction method combining multispectral imagery, AI, and growth models.
Abstract: In the digital era, effective Transaction Fraud Detection (TFD) is essential to ensuring financial security. The considerable class imbalance, with legitimate transactions vastly ...
Introduction Antimicrobial stewardship efforts in low- and middle-income countries (LMICs) largely focus on qualified ...
TAR 2.0 is likely the most widely used analytic technology for reviewing large document collections for production (although ...
Cryo-electron microscopy (cryo-EM) can help scientists determine the three-dimensional structure of proteins in unprecedented detail. Jacques Dubochet, former group leader at EMBL, shared the 2017 ...
MIT researchers created a technique that captures chemical arrangements across materials to improve predictions of how metal ...
From replacement selection to BRD resilience, tissue sampling units provide a fast, clean and reliable path to the genomic ...
A technology developed at the Technion enables ordinary users to create realistic video clips intuitively, without the need ...
Abstract: The increasing use of electrical machines (EM) across industrial sectors requires reliable ground fault (GF) detection schemes. In this context, stator GFs resulting from insulation ...
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