A comprehensive new review maps how deep learning can fuse social media and satellite data to make disaster response faster...

An interpretable machine-learning study of Shahu Lake shows that the drivers of algal blooms shift with the seasons, from long-term...

A new label-scarce graph AI framework reliably detects deep, subtle mineralization anomalies at the Kalatongke copper-nickel deposit using only 906...

Researchers have developed a scalable machine learning method that uses time-series clustering to automatically identify visual search strategies from raw...

A multi-center Chinese study shows that radiomics and deep learning models applied to routine carotid CT angiography can predict plaque...

A new tensor decomposition framework dynamically compresses and decompresses neural network layers during training, achieving 95.81 percent accuracy in 12...

Researchers have developed P2CE, a model-agnostic algorithm that generates counterfactual explanations for machine learning decisions that are both plausible and...

An interpretable machine learning model trained on 20 years of rural Spanish registry data outperforms logistic regression in predicting 30-day...

Researchers have developed AI-TEACH, a multimodal AI framework that detects and scores classroom distraction in real time with 90% accuracy...

Researchers have developed an AI-driven trust and decision-making framework that uses software-defined networking and the Bat Algorithm to select secure,...