Discretization of Learned NETT Regularization for Solving Inverse Problems

Deep learning based reconstruction methods deliver outstanding results for solving inverse problems and are therefore becoming increasingly important. A recently invented class of learning-based reconstruction methods is the so-called NETT (for Network Tikhonov Regularization), which contains a trai...

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Detalles Bibliográficos
Autores principales: Antholzer, Stephan, Haltmeier, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8625045/
https://www.ncbi.nlm.nih.gov/pubmed/34821870
http://dx.doi.org/10.3390/jimaging7110239

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8625045/
https://www.ncbi.nlm.nih.gov/pubmed/34821870
http://dx.doi.org/10.3390/jimaging7110239

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