New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer quality, enabling early wafer screening and optimized production paths. Using ...

Researchers have demonstrated, for the first time, that transfer learning can significantly enhance material Z-class identification in muon tomography, even in scenarios with limited or completely ...

In machine learning, privacy risks often emerge from inference-based attacks. Model inversion techniques can reconstruct sensitive training data from model outputs. Membership inference attacks allow ...

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

AI-powered document processing automates data extraction, classification, and validation with 95-99% accuracyMarket projected ...

Could the Innovation in Non-Human Identities Be the Key to Enhanced Secrets Security? Where progressively leaning towards automation and digital transformation, how can we ensure that the creation and ...

How Do Non-Human Identities Impact Security in a Cloud Environment? Have you ever pondered how non-human identities (NHIs) play a role? Where organizations migrate to cloud-based systems, security is ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...