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Odstraňování šumu v obraze pomocí metod hlubokého učení / Removing noise in images using deep learning methods

This thesis focuses on comparing methods of denoising by deep learning and their implementation. In the last few years, it has become clear that it is not necessary to have paired data, as for noisy and clean pictures, to train convolution neural networks but it is sufficient to have only noisy pictures for denoising in particular cases. By using methods described in this thesis it is possible to effectively remove i.e. additive Gaussian noise and what more, it is possible to achieve better results than by using statistic methods, which are being used for denoising these days.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:442579
Date January 2021
CreatorsStrejček, Jakub
ContributorsJakubíček, Roman, Vičar, Tomáš
PublisherVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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