Survey on CNN based super resolution methods

Journal La Multiapp

View Publication Info
Field Value
Title Survey on CNN based super resolution methods
Creator Kazem, Rafaa Amen
Suad, Jamila H.
Abdulbaqi, Huda Abdulaali
Subject CNN
Description Super Resolution is a field of image analysis that focuses on boosting the resolution of photographs and movies without compromising detail or visual appeal, instead enhancing both. Multiple (many input images and one output image) or single (one input and one output) stages are used to convert low-resolution photos to high-resolution photos. The study examines super-resolution methods based on a convolutional neural network (CNN) for super-resolution mapping at the sub-pixel level, as well as its primary characteristics and limitations for noisy or medical images.
Publisher Newinera Publisher
Date 2021-09-27
Type info:eu-repo/semantics/article
Peer-reviewed Article
Format application/pdf
Source Journal La Multiapp; Vol. 2 No. 4 (2021): Journal La Multiapp; 27-33
Language eng
Rights Copyright (c) 2021 Journal La Multiapp

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us


Copyright © 2015-2018 Simon Fraser University Library