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U-Net: Convolutional Networks for Biomedical Image Segmentation

Lecture Notes in Computer Science(2015)10.1007/978-3-319-24574-4_28Source: DataRank Database

U-Net: Convolutional Networks for Biomedical Image Segmentation is a research paper published in Lecture Notes in Computer Science (2015). On theSindex it has a DataRank of 1.7. It has been cited 86,331 times.

N/A

1.7DataRank · unranked

Scored on demand from live citation data

Open Access86,331 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (1 grants)OA: bronzeTopics (7)IDs (PubMed)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

1.7

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

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Authors (3)

Philipp Fischer ORCID,Thomas Brox ORCID,Olaf Ronneberger ORCID

Live enrichment

PubMed:19162232

Deutsche Forschungsgemeinschaft

Grant: 39236281/EXC 294

BIOSS Centre for Biological Signalling Studies - from Analysis to Synthesis

bronzeLicense: Springer TDM

publisherhttps://link.springer.com/content/pdf/10.1007/978-3-319-24574-4_28.pdf

publisherhttp://link.springer.com/content/pdf/10.1007/978-3-319-24574-4_28

https://doi.org/10.1007/978-3-319-24574-4_28

http://arxiv.org/pdf/1505.04597

https://dx.doi.org/10.48550/arxiv.1505.04597

Fields of Study

03 medical and health sciences0302 clinical medicine0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

FOS: Computer and information sciencesComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern Recognition