Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Stacked U-Nets: A No-Frills Approach to Natural Image Segmentation
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1804.10343.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T11:06:43.073761Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T17:31:04.603216Z
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 f2aa629e-388a-4fc7-bf0f-7d98b4763b18 · inbound
SPGNet: Semantic Prediction Guidance for Scene Parsing cites this paper.
SPGNet: Semantic Prediction Guidance for Scene Parsing Stacked U-Nets: A No-Frills Approach to Natural Image Segmentation
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T11:06:43.073761Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 207f9e14-8507-4fd4-96e1-55ade8525b30 · inbound
Hierarchical-embedding autoencoder with a predictor (HEAP) as efficient architecture for learning long-term evolution of complex multi-scale physical systems cites this paper.
Hierarchical-embedding autoencoder with a predictor (HEAP) as efficient architecture for learning long-term evolution of complex multi-scale physical systems Stacked U-Nets: A No-Frills Approach to Natural Image Segmentation
Reference 68
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:27:44.102317Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 93d06cfe-6cf2-49f3-bba3-41019470b0e6 · inbound
Deep Wave Network for Modeling Multi-Scale Physical Dynamics cites this paper.
Deep Wave Network for Modeling Multi-Scale Physical Dynamics Stacked U-Nets: A No-Frills Approach to Natural Image Segmentation
Reference 75
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T22:43:52.004158Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.