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

Research article (Neural Computing and Applications, 2022) · cited 100× · AI/ML
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R2U++: a multiscale recurrent residual U-Net with dense skip connections for medical image segmentation

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R2U++: a multiscale recurrent residual U-Net with dense skip connections for medical image segmentation is a scholarly article[1].

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  • R2U++: a multiscale recurrent residual U-Net with dense skip connections for medical image segmentation's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). R2U++: a multiscale recurrent residual U-Net with dense skip connections for medical image segmentation. Retrieved May 24, 2026, from https://4ort.xyz/entity/r2u-a-multiscale-recurrent-residual-u-net-with-dense-skip-connections-for-medical-image-segmentation
MLA “R2U++: a multiscale recurrent residual U-Net with dense skip connections for medical image segmentation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/r2u-a-multiscale-recurrent-residual-u-net-with-dense-skip-connections-for-medical-image-segmentation.
BibTeX @misc{4ortxyz_r2u-a-multiscale-recurrent-residual-u-net-with-dense-skip-connections-for-medical-image-segmentation_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{R2U++: a multiscale recurrent residual U-Net with dense skip connections for medical image segmentation}}, year = {2026}, url = {https://4ort.xyz/entity/r2u-a-multiscale-recurrent-residual-u-net-with-dense-skip-connections-for-medical-image-segmentation}, note = {Accessed: 2026-05-24}}
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