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Paper Citation Record · LEDGER

A Comprehensive Review of U-Net and Its Variants: Advances and Applications in Medical Image Segmentation

As of 10 August 2026, this Paper Citation Record lists 5 of 5 outbound references and 0 inbound Pith citation observations for arXiv:2502.06895.

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

pith.paper-citation-record.v1
2502.06895 v1

Coverage vector

measured 5 of 5 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:33:05.009864Z

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

5 of 5 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8402f6e1-d00c-42f2-930a-003be26047a9 · outbound

This paper cites an unresolved cited work.

A Comprehensive Review of U-Net and Its Variants: Advances and Applications in Medical Image Segmentation Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-08T17:33:05.140287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T17:33:04.998538Z digest=sha256:b77af2512c4d5d7ba3180fd25b207a489b6b9a3285b69a1961359640c3e11204

Observation d9848894-7b78-404f-9f13-b45b21f618e1 · outbound

This paper cites In recent years, U-Net and variant network models have shown excellent performance in medical dataset segmentation.

A Comprehensive Review of U-Net and Its Variants: Advances and Applications in Medical Image Segmentation In recent years, U-Net and variant network models have shown excellent performance in medical dataset segmentation

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:33:05.046674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T17:33:05.005454Z digest=sha256:80d8d0ffe752c5d747666c6ad6c08a8cfcfbd5c2a06501536e982eb04331133b

Observation c75555e4-47c6-4086-9afd-a5d7411ae474 · outbound

This paper cites Additionally, manual annotation has difficulty avoiding subjective errors.

A Comprehensive Review of U-Net and Its Variants: Advances and Applications in Medical Image Segmentation Additionally, manual annotation has difficulty avoiding subjective errors

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:33:05.056253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T17:33:05.002032Z digest=sha256:d4811f0d933e4fea052f1eee2a37a0d0ab96957c8eeadb257029d52079f80e0c

Observation 49dc6831-27d9-442c-9be7-85cad8e7548e · outbound

This paper cites U-shaped.

A Comprehensive Review of U-Net and Its Variants: Advances and Applications in Medical Image Segmentation U-shaped

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:33:05.149529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T17:33:04.993205Z digest=sha256:0ea572cea55a6fe63551cc5cbcf9c081c4a8ebaf99972dfc9083bce800cc6978

Observation cc01ae18-be28-47a8-8bc6-e0676a391c5c · outbound

This paper cites Self-aware and Cross-sample Prototypical Learning for Semi-supervised Medical Image Segmentation.

A Comprehensive Review of U-Net and Its Variants: Advances and Applications in Medical Image Segmentation Self-aware and Cross-sample Prototypical Learning for Semi-supervised Medical Image Segmentation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-08T17:33:05.009864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:33:05.009864Z digest=sha256:eb0c4ab38d7dfd8ea8c797caeb61780cb497109a81c62794cc90324a356c3437

Pith citing papers

No inbound Pith citation observations are available.