Tag: multi-scale feature fusion

Chinese researchers have developed CDCNet, a deep learning framework that recognizes fine-grained barefoot footprint regions with 83.2 percent mean Average ...

Researchers in China have developed HA-DETR, a transformer-based detector that adaptively enhances features at different semantic levels to overcome blur, ...

Researchers in China have developed UG-HRNet, a lightweight high-resolution network that pairs a unified guidance deformable convolution with an alternating ...

Researchers in China have developed MAF-Net, a multi-scale attention fusion network that achieves a record Dice score of 85.47 percent ...

Researchers in China have developed HSF-Net, a hybrid-scale fusion deep learning network that achieved an 83.4 percent Dice score in ...

Researchers in China have developed NAHFormer, a transformer-based segmentation framework using neighborhood attention and hierarchical feature fusion that outperforms state-of-the-art ...

Fine-grained visual classification has long been one of the most stubborn problems in computer vision, and a new study published ...