Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
U-Net Using Stacked Dilated Convolutions for Medical Image Segmentation
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2004.03466.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:16:32.998967Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T10:26:30.502415Z
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 023c7380-f831-41d6-b7a0-5f177fffab04 · inbound
A Deep Learning Framework for Two-Dimensional, Multi-Frequency Propagation Factor Estimation cites this paper.
A Deep Learning Framework for Two-Dimensional, Multi-Frequency Propagation Factor Estimation U-Net Using Stacked Dilated Convolutions for Medical Image Segmentation
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:16:32.998967Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cfc59011-cec5-4369-a1e0-8a48a7660187 · inbound
InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation cites this paper.
InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation U-Net Using Stacked Dilated Convolutions for Medical Image Segmentation
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T01:02:21.163533Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e261347-d164-45de-9318-d39c81a77b63 · inbound
3D Reconstruction Techniques in the Manufacturing Domain: Applications, Research Opportunities and Use Cases cites this paper.
3D Reconstruction Techniques in the Manufacturing Domain: Applications, Research Opportunities and Use Cases U-Net Using Stacked Dilated Convolutions for Medical Image Segmentation
Reference 190
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:26:30.505471Z
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.