DeepSR: A deep learning tool for image super resolution

Autor: Hakan Temiz
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: SoftwareX, Vol 21, Iss , Pp 101261- (2023)
Druh dokumentu: article
ISSN: 2352-7110
DOI: 10.1016/j.softx.2022.101261
Popis: An open source tool is introduced that provides a versatile environment to meet the needs of researchers in developing deep learning (DL) algorithms for single image super-resolution reconstruction (SISR). The processes of SISR were carefully studied, unified and integrated to create software that can be used by the community for any type of imaging method such as aerial, medical, optical, etc. DeepSR allows easy implementation of SISR application with rapidly prototyped DL models, and detailed reporting and recording of the results. The entire experiment can be done with simple command line scripts. It can be easily extended by user-defined metrics, augmentations, callbacks, etc.
Databáze: Directory of Open Access Journals