Understanding Deep Image Prior

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F23%3A00369787" target="_blank" >RIV/68407700:21340/23:00369787 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Understanding Deep Image Prior
Original language description
Inverse problems in imaging, like denoising, inpainting or superresolution usually require a suitable regularization or a prior to achieve good reconstruction results. It was shown that untrained neural networks can replace traditional handcrafted priors and achieve superior performance. This contribution will focus on Deep Image Prior, the pioneering work utilizing untrained neural priors, its applications for image reconstruction problems, and possible explanations of its success.
Czech name
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Czech description
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Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
SPMS 2022/23 Stochastic and Physical Monitoring Systems, Proceedings of the international conferences
ISBN
978-80-01-07250-9
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
37-43
Publisher name
České vysoké učení technické v Praze
Place of publication
Praha
Event location
Sloup v Čechách
Event date
Jun 26, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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