Tag: super-resolution

A deep learning super-resolution MRI model improved preoperative predictions of lymphovascular space invasion in early-stage cervical cancer patients.

A hybrid deep learning framework combining lightweight super-resolution, transformer-based masked attention, and density regression significantly improves platelet detection and counting ...

Researchers introduced Fourier-Enhanced TecoGAN, combining architectural upgrades with Fourier and gradient losses to improve video super-resolution performance on benchmark evaluations.

A new AI method imputes missing slices into 3D brain reconstructions built from dissection photographs, yielding sharper anatomical detail and ...

A new conditional diffusion model called DSR-STRDiff reconstructs high-resolution elevation data from coarse inputs, reporting the best metrics among compared ...

Researchers in China have built an explainable deep learning model that analyzes contrast-enhanced CT scans to predict whether non-muscle-invasive bladder ...

A new harmonization-based super-resolution workflow shows that cross-sensor radiometric calibration, not network architecture, is the largest contributor to sharpening free ...

Researchers have developed a pixel-segmenting imaging method that maps intra-pixel quantum efficiency using evolutionary algorithms, reducing the effective sampling unit ...

A new measurement-driven framework reveals that AI-powered video enhancement fundamentally reshapes streaming efficiency, with energy outcomes swinging from 85 percent ...

A hybrid graph neural network and deep unrolling architecture achieves 98 percent success in super-resolution direction-of-arrival estimation while remaining robust ...