Japanese researchers have developed and internally validated prediction models that estimate, at the moment of Medical Emergency Team activation, which...

A new multimodal deep learning framework fuses Log-Mel spectrograms and BERT embeddings through self-attention to automatically score spoken English fluency...

Researchers have combined neutrosophic set theory with deep feature geometry to give pretrained neural networks an interpretable, three-part measure of...

Researchers have developed a CNN-BiLSTM-Attention hybrid neural network optimized by an improved antlion algorithm that diagnoses and predicts transformer faults...

A new RGB-D perception-to-action framework called E-YOLOv11-RGBD raised robotic greenhouse harvesting success from 51.7 to 92.5 percent by converting AI...

Researchers have developed a physics-informed, uncertainty-aware graph neural network that predicts jet engine remaining useful life with record robustness under...

A large-scale study argues that machine learning performance should be reported as distributions with confidence intervals on quantiles rather than...

Researchers at Guangdong University of Technology have developed DP-MVAD, a dual-path multi-view framework that disentangles trends from perturbations and fuses...

Researchers in China have developed a self-supervised graph neural network that classifies the urgency of urban patrol cases without any...

A new benchmark study shows that data augmentation lifts pre-trained deep learning models to up to 98.06% accuracy in classifying...