Tag: attention mechanism

Researchers at Central South University have created a hybrid deep learning model that lets mobile agricultural robots accurately forecast pollutant ...

A new parallel Transformer-CNN architecture called TCNNISTD achieves state-of-the-art accuracy and real-time speed in detecting infrared targets smaller than ten ...

A two-stage imaging and deep learning framework detects and grades infestations of four greenhouse pests, distilling 248 spectral bands into ...

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

A new self-supervised framework combining joint-embedding prediction and bidirectional Mamba learns diagnostic ECG representations without labeled data, outperforming prior baselines ...

A spatiotemporal attention network that reads fNIRS blood-oxygen signals while patients listen to music classifies levels of consciousness with 88.72 ...

A new machine learning model called DBFP combines LSTM networks, attention mechanisms, and non-linear regularization to predict which software features ...

A new FCN-GRU-Attention deep learning model with a confidence correction mechanism identifies overlapping composite power quality disturbances with over 99 ...

Researchers have developed S2Fusion, a local-to-global framework that improves infrared and visible image fusion through cross-modal dynamic kernels and a ...

Korean researchers have built a hybrid Vision Transformer and CNN generative model that enhances ultrasound image quality with state-of-the-art fidelity ...