Enhancing Image Resolution With Generative Adversarial Networks

dc.authorscopusid 14632851900
dc.contributor.author Yildiz,B.
dc.contributor.other Software Engineering
dc.date.accessioned 2024-07-05T15:49:57Z
dc.date.available 2024-07-05T15:49:57Z
dc.date.issued 2022
dc.department Atılım University en_US
dc.department-temp Yildiz B., Atilim University, Department of Software Engineering, Ankara, Turkey en_US
dc.description.abstract Super-resolution is the process of generating high-resolution images from low-resolution images. There are a variety of practical applications used in real-world problems such as high-definition content creation, surveillance imaging, gaming, and medical imaging. Super-resolution has been the subject of many researches over the past few decades, as improving image resolution offers many advantages. Going beyond the previously presented methods, Generative Adversarial Networks offers a very promising solution. In this work, we will use the Generative Adversarial Networks-based approach to obtain 4x resolution images that are perceptually better than previous solutions. Our extensive experiments, including perceptual comparison, Peak Signal-to-Noise Ratio, and classification success metrics, show that our approach is quite promising for image super-resolution. © 2022 IEEE. en_US
dc.identifier.citationcount 1
dc.identifier.doi 10.1109/UBMK55850.2022.9919520
dc.identifier.endpage 109 en_US
dc.identifier.isbn 978-166547010-0
dc.identifier.scopus 2-s2.0-85141825651
dc.identifier.startpage 104 en_US
dc.identifier.uri https://doi.org/10.1109/UBMK55850.2022.9919520
dc.identifier.uri https://hdl.handle.net/20.500.14411/4064
dc.institutionauthor Yıldız, Beytullah
dc.language.iso en en_US
dc.publisher Institute of Electrical and Electronics Engineers Inc. en_US
dc.relation.ispartof Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022 -- 7th International Conference on Computer Science and Engineering, UBMK 2022 -- 14 September 2022 through 16 September 2022 -- Diyarbakir -- 183844 en_US
dc.relation.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 2
dc.subject Deep Learning en_US
dc.subject Generative Adversarial Networks en_US
dc.subject Image Processing en_US
dc.subject Machine Learning en_US
dc.subject Super Resolution en_US
dc.title Enhancing Image Resolution With Generative Adversarial Networks en_US
dc.type Conference Object en_US
dspace.entity.type Publication
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relation.isAuthorOfPublication.latestForDiscovery 8eb144cb-95ff-4557-a99c-cd0ffa90749d
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relation.isOrgUnitOfPublication.latestForDiscovery d86bbe4b-0f69-4303-a6de-c7ec0c515da5

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