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UNet++: A Nested U-Net Architecture for Medical Image Segmentation
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U-Net: Convolutional Networks for Biomedical Image Segmentation
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“UNet++ [19] represents a convolutional encoder–decoder architecture with nested dense skip connections.”
Metadata
- Authors
- Zhou, Z., Rahman Siddiquee, M. M., Tajbakhsh, N., & Liang, J.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Volume
- 11045
- Pages
- 3-11
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2884436604
- Cited by
- 9,610
- References
- 4
- FWCI
- 98.85
- Type
- conference paper
- Language
- en
- Open access
- bronze
- Licence
- www.springernature.com/gp/researchers/text-and-data-mining (tdm)
- www.springernature.com/gp/researchers/text-and-data-mining (vor)
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