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

A new neural framework called CMCE+BK combines extended candidate events with multi-level background knowledge to dramatically improve the mining of...

University of Reading researchers used an AI weather model to replay the storm forecast behind the D-Day invasion decision, finding...

A 25-year review of artificial intelligence applications in streamflow forecasting reveals that feed-forward neural networks dominate the field while long-range...

Researchers argue that when AI demonstrably outperforms humans by our own standards, the burden of proof shifts to those insisting...

A new systematic review argues that training-free neural architecture search can slash the enormous computational cost of AI model design...

Researchers have developed an interpretable hierarchical pipeline combining Gaussian filtering, YCbCr-based CLAHE enhancement, K-means nuclei segmentation, and SVM classification that...

Researchers at UCLA and Cedars-Sinai developed a computer vision AI that classifies laparoscopic peg transfer performance with 84 percent accuracy,...

Researchers in China have developed a Transformer-CNN deep learning framework that segments and grades gastric intestinal metaplasia in whole slide...

A lightweight hybrid framework combining randomized convolutional feature extraction with extreme learning machines classifies vehicles in fog, rain, and drone...