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pro vyhledávání: '"Mark Matthewman"'
Autor:
Gerd Heilemann, Mark Matthewman, Peter Kuess, Gregor Goldner, Joachim Widder, Dietmar Georg, Lukas Zimmermann
Publikováno v:
Zeitschrift für Medizinische Physik, Vol 32, Iss 3, Pp 361-368 (2022)
Purpose: For image translational tasks, the application of deep learning methods showed that Generative Adversarial Network (GAN) architectures outperform the traditional U-Net networks, when using the same training data size. This study investigates
Externí odkaz:
https://doaj.org/article/9e283f98eaf04e05a899a51a275ad360
Autor:
Gerd Heilemann, Mark Matthewman, Peter Kuess, Gregor Goldner, Joachim Widder, Dietmar Georg, Lukas Zimmermann
Publikováno v:
Zeitschrift fur medizinische Physik. 32(3)
For image translational tasks, the application of deep learning methods showed that Generative Adversarial Network (GAN) architectures outperform the traditional U-Net networks, when using the same training data size. This study investigates whether
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::37b1ea03e2cb02ec7a94a23e4b905b1e
https://pubmed.ncbi.nlm.nih.gov/34930685
https://pubmed.ncbi.nlm.nih.gov/34930685