A Unified Framework for Unsupervised Backlight and Lowlight Image Enhancement via CLIP-Guided Prompt Learning and Symmetric Residual UNet
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| التنسيق: | masterThesis |
| منشور في: |
2020
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://eprints.kfupm.edu.sa/id/eprint/143618/1/Yasmin_Yasin_Master_Thesis_202214360_Final.pdf |
| الوسوم: |
إضافة وسم
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| _version_ | 1868869873608687616 |
|---|---|
| author | unknown |
| author_facet | unknown |
| author_role | author |
| dc.creator.*.fl_str_mv | unknown |
| dc.date.*.fl_str_mv | 2020 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/143618/1/Yasmin_Yasin_Master_Thesis_202214360_Final.pdf A Unified Framework for Unsupervised Backlight and Lowlight Image Enhancement via CLIP-Guided Prompt Learning and Symmetric Residual UNet. Masters thesis, King Fahd University of Petroleum and Minerals. |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/143618/ |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Computer Research |
| dc.title.none.fl_str_mv | A Unified Framework for Unsupervised Backlight and Lowlight Image Enhancement via CLIP-Guided Prompt Learning and Symmetric Residual UNet |
| dc.type.none.fl_str_mv | Thesis NonPeerReviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/masterThesis |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| id | KFUPM_6b43fcfbfb7d43b80ffe806c21c3915f |
| identifier_str_mv | A Unified Framework for Unsupervised Backlight and Lowlight Image Enhancement via CLIP-Guided Prompt Learning and Symmetric Residual UNet. Masters thesis, King Fahd University of Petroleum and Minerals. |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai:eprints.kfupm.edu.sa:143618 |
| publishDate | 2020 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
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| spelling | A Unified Framework for Unsupervised Backlight and Lowlight Image Enhancement via CLIP-Guided Prompt Learning and Symmetric Residual UNetComputerResearchThesisNonPeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/143618/1/Yasmin_Yasin_Master_Thesis_202214360_Final.pdf A Unified Framework for Unsupervised Backlight and Lowlight Image Enhancement via CLIP-Guided Prompt Learning and Symmetric Residual UNet. Masters thesis, King Fahd University of Petroleum and Minerals. enhttps://eprints.kfupm.edu.sa/id/eprint/143618/2020info:eu-repo/semantics/openAccessunknownoai:eprints.kfupm.edu.sa:1436182026-06-21T09:26:50Z |
| spellingShingle | A Unified Framework for Unsupervised Backlight and Lowlight Image Enhancement via CLIP-Guided Prompt Learning and Symmetric Residual UNet unknown Computer Research |
| status_str | publishedVersion |
| title | A Unified Framework for Unsupervised Backlight and Lowlight Image Enhancement via CLIP-Guided Prompt Learning and Symmetric Residual UNet |
| title_full | A Unified Framework for Unsupervised Backlight and Lowlight Image Enhancement via CLIP-Guided Prompt Learning and Symmetric Residual UNet |
| title_fullStr | A Unified Framework for Unsupervised Backlight and Lowlight Image Enhancement via CLIP-Guided Prompt Learning and Symmetric Residual UNet |
| title_full_unstemmed | A Unified Framework for Unsupervised Backlight and Lowlight Image Enhancement via CLIP-Guided Prompt Learning and Symmetric Residual UNet |
| title_short | A Unified Framework for Unsupervised Backlight and Lowlight Image Enhancement via CLIP-Guided Prompt Learning and Symmetric Residual UNet |
| title_sort | A Unified Framework for Unsupervised Backlight and Lowlight Image Enhancement via CLIP-Guided Prompt Learning and Symmetric Residual UNet |
| topic | Computer Research |
| url | https://eprints.kfupm.edu.sa/id/eprint/143618/1/Yasmin_Yasin_Master_Thesis_202214360_Final.pdf |