Paper Citation Record · LEDGER

UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2004.08790.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2004.08790 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:50:51.126071Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-02T16:07:08.708396Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0f776776-f7bf-42bb-900f-fba3c210f5b7 · inbound

A Comprehensive Study on Medical Image Segmentation using Deep Neural Networks cites this paper.

A Comprehensive Study on Medical Image Segmentation using Deep Neural Networks UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:51.126071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 605c6a3d-08e5-4bbd-ab21-9d058fc3bd38 · inbound

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers cites this paper.

Barlow-Swin: Toward a novel siamese-based segmentation architecture using Swin-Transformers UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T23:02:49.957998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 938b3888-7179-463c-92b0-d03891b3c3fc · inbound

Compute-Optimal Network Design for Echocardiography Myocardial Segmentation and Perfusion Quantification using Neural Scaling Laws cites this paper.

Compute-Optimal Network Design for Echocardiography Myocardial Segmentation and Perfusion Quantification using Neural Scaling Laws UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:07:08.710504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c3fe008a-ae19-43ce-ab41-449f05a91eab · inbound

DCSNet: Multiscale Feature Aggregation for Small Medical Object Segmentation with Detection-guided Hierarchical Cropping cites this paper.

DCSNet: Multiscale Feature Aggregation for Small Medical Object Segmentation with Detection-guided Hierarchical Cropping UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:35:48.652929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.