Tag: Transformer

A hybrid attention model combined six years of field observations with orchard geography to forecast occurrence levels and intensity for ...

A compact hybrid Transformer-graph attention autoencoder reconstructs downhole geomechanical states from unlabelled drilling data, outperforming standalone models and surviving simulated ...

Researchers in China have developed an improved deep reinforcement learning framework that jointly optimizes trajectory prediction and lane-changing decisions, achieving ...

Researchers at the Vellore Institute of Technology developed three hybrid deep learning models combining convolutional networks, transformers, and clinical metadata ...

A multicenter study shows a 2.5D Transformer-based AI framework combining clinical data, MRI radiomics and deep learning can reliably distinguish ...

A new transfer learning framework measures cultural distance between audiences and uses it to rewrite film, tourism, and heritage content ...

A new difficulty-aware Transformer framework jointly optimized by particle swarm intelligence improves sports score trend prediction while attributing forecasts to ...

Researchers in Trieste embedded anatomical rules as logical constraints in a transformer segmentation model, boosting accuracy and morphological coherence in ...

Every large power transformer hums with invisible activity. Deep inside its core and windings, electromagnetic losses deposit heat continuously, shaping ...

A transformer-based deep-learning pipeline called ProFormer classifies single-cell and plasma proteomes directly from raw mass-spectrometry fingerprints, outperforming CNNs and enabling ...