Tag: Transformer

Researchers at Tsinghua University have developed a Series Saliency module guided by large language models that improves the accuracy and ...

Researchers have developed a transformer-based framework with local-global attention that identifies writers from scanned handwriting without reading the text, achieving ...

A systematic study shows that Z-score normalization, applied after artifact removal, is essential for Transformer models to decode movement from ...

Researchers have developed ZD-HybridNet, a hybrid Transformer-LSTM deep learning framework that detects attack categories withheld from training and explains its ...

Researchers have developed a hybrid deep learning architecture combining graph neural networks, Transformers, and variational autoencoders to detect and explain ...

A new dual-stream deep learning framework fuses spatiotemporal brain activity with dynamic functional connectivity to classify neurological disease severity from ...

Researchers at the University of Tabriz have developed GCAT, a graph-convolutional adversarial transformer that detects anomalies in multivariate sensor data ...

A new decoupled graph-augmented transformer architecture separates static road topology from dynamic traffic patterns to reduce optimization interference and achieve ...

Researchers at Shanghai Maritime University have developed RPCV, a deep clustering method that uses transformer-based cross-view attention and entropy-constrained prototype ...

Physicists have used a GPT-style transformer to generate silicon tracker hits for the first time, achieving tracking performance comparable to ...