Tag: cross-attention

A dual-graph deep learning network that hard-codes petroleum physics alongside learned statistics cuts oil production prediction error to about 20 ...

Researchers have unveiled MiRAGE, a parameter-efficient AI framework that adapts its computational depth to each satellite image and uses CLIP ...

A dual-branch deep learning framework called QICAF-Net borrows the mathematics of quantum states to fuse retinal image features, achieving competitive ...

A new Transformer-based dual-domain AI framework reconstructs high-quality CT images from sparse projection views, potentially reducing patient radiation exposure while ...

A new dual-modality deep learning framework called DHF-DTI combines sequence and graph data with cross-attention fusion and supervised contrastive learning ...

A new multiscale cross attention network predicts electromagnetic coupling in hot-pressed In-Pb heterostructures with record accuracy and enables experimentally validated ...

Researchers have integrated transformer attention mechanisms into learned primal-dual PET reconstruction, achieving cleaner images from noisy low-count scanner data.

A new Genome Biology study introduces Pep2Net, a platform combining a knowledge base built from 52 peptide databases with a ...

Researchers have unveiled EEG-UDAF, an unsupervised domain adaptation framework that fuses dual-view frequency features with spatio-temporal modeling to recognize emotions ...

Researchers in Vietnam have built a hybrid vision-language AI that diagnoses grapevine diseases with 98.7 percent accuracy while explaining its ...