DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 예종철 | - |
dc.contributor.author | Kim, Sehui | - |
dc.contributor.author | 김세희 | - |
dc.date.accessioned | 2024-07-30T19:30:37Z | - |
dc.date.available | 2024-07-30T19:30:37Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1096056&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/321351 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 김재철AI대학원, 2024.2,[iii, 28 p. :] | - |
dc.description.abstract | We propose FD3, a fundus image enhancement method based on direct diffusion bridges, which can cope with a wide range of complex degradations, including haze, blur, noise, and shadow. We first propose a synthetic forward model through a human feedback loop with board-certified ophthalmologists for maximal quality improvement of low-quality in-vivo images. Using the proposed forward model, we train a robust and flexible diffusion-based image enhancement network that is highly effective as a stand-alone method, unlike previous diffusion model-based approaches which act only as a refiner on top of pre-trained models. Through extensive experiments, we show that FD3 establishes the new state-of-the-art not only on synthetic degradations but also on in vivo studies with low-quality fundus photos taken from patients with cataracts or small pupils. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | 확산 모델▼a안저 사진 품질 향상▼a직접 확산 모델 | - |
dc.subject | Diffusion model▼aFundus image enhancement▼aDirect diffusion bridge | - |
dc.title | Fundus image enhancement through direct diffusion bridges | - |
dc.title.alternative | 직접 확산 모델을 이용한 안저 사진 품질 향상 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :김재철AI대학원, | - |
dc.contributor.alternativeauthor | Ye, Jong Chul | - |
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