A Simple Scaling Step Makes or Breaks AI That Reads Brain Signals for Movement
A systematic study shows that Z-score normalization, applied after artifact removal, is essential for Transformer models to decode movement from ...
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 ...
Researchers at the University of Isfahan have unveiled a wearable glove system and an ultra-compact transformer that recognize continuous multi-digit ...
A new hybrid model called TG-Parser combines Transformer encoders with graph convolutional networks to achieve record-setting accuracy in English grammatical ...
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© 2026 Scienmag - Science Magazine