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 ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

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

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 ...

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 ...

Bangladeshi researcher Md Masum Billah is advancing the application of artificial intelligence in healthcare and digital security, focusing on practical solutions for real-world challenges, said a ...

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 addition to improved performance from individual sensing technologies, including radar and light detection and ranging ...

Market valued at $1.68B in 2024, projected to reach $4.58B by 2033 at 13.4% CAGR, driven by chronic wound prevalence ...

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

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