Work

SwinMED: Edge-texture enhanced SwinIR for medical image super-resolution

Year: 2026

Type: article

Source: Knowledge-Based Systems

DOI: 10.1016/j.knosys.2026.116665

Authors: Samet Aymaz, Şeyma Aymaz

Institution: Karadeniz Technical University

Language: English

Topic: Advanced Image Processing Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W7171563427

FWCI:

Cites: 75

Cited by:

Related to: 10