R2U++: a multiscale recurrent residual U-Net with dense skip connections for medical image segmentation

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1433-3058

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: R2U++: a multiscale recurrent residual U-Net with dense skip connections for medical image segmentation ; day:3 ; month:6 ; year:2022 ; pages:1-17
Neural computing & applications ; (3.6.2022), 1-17

Creator: Mubashar, Mehreen
Ali, Hazrat
Grönlund, Christer
Azmat, Shoaib

Contributor: SpringerLink (Online service)

DOI: 10.1007/s00521-022-07419-7

URN: urn:nbn:de:101:1-2022080223065151732728

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:26 AM CEST

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Mubashar, Mehreen
Ali, Hazrat
Grönlund, Christer
Azmat, Shoaib
SpringerLink (Online service)

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R2U++: a multiscale recurrent residual U-Net with dense skip connections for medical image segmentation

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