Please use this identifier to cite or link to this item: http://thuvienso.dut.udn.vn/handle/DUT/4099
DC FieldValueLanguage
dc.contributor.advisorPham, Cong Thang, PhD.
dc.contributor.authorLe, Thanh Phuong
dc.date.accessioned2024-11-06T05:15:15Z-
dc.date.available2024-11-06T05:15:15Z-
dc.date.issued2022
dc.identifier.urihttp://thuvienso.dut.udn.vn/handle/DUT/4099-
dc.descriptionDA.FA.22.079 ; 63 p.vi
dc.description.abstractPhoto recovery is the process of rebuilding lost or degraded parts of photos and videos. In the case of a valuable painting, this task will be performed by a skilled artist restoring the painting. In the world of information technology, image recovery refers to the application of complex algorithms to replace lost or damaged parts of image data. Image recovery involves removing noise and sometimes algorithms using ideas about denoising, but image restoration is fundamentally a different matter from denoising. Noise areas usually have some information about the original image, but in image recovery, some areas are completely lost in the original image data. The focus of this thesis is to understand the problems related to recovering noisy grayscale images, to study some algorithms to recover noisy gray images, and to focus on understanding deep learning models to recover images at the beginning. The algorithm will be tested with a program that uses the Python language.vi
dc.language.isoenvi
dc.publisherTrường Đại học Bách khoa - Đại học Đà Nẵngvi
dc.subjectRestore digital imagevi
dc.subjectDeep learningvi
dc.subjectImage processingvi
dc.subjectPython languagevi
dc.titleRestore digital images using deep learningvi
dc.typeĐồ ánvi
item.openairetypeĐồ án-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextrestricted-
item.fulltextCó toàn văn-
item.cerifentitytypePublications-
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