Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
LadderNet: Multi-path networks based on U-Net for medical image segmentation
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1810.07810.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T10:28:30.749888Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T06:19:37.372839Z
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 53761b8c-9dbe-4c81-a058-5db130f0cd94 · inbound
Efficient Structurally-Strengthened Generative Adversarial Network for MRI Reconstruction cites this paper.
Efficient Structurally-Strengthened Generative Adversarial Network for MRI Reconstruction LadderNet: Multi-path networks based on U-Net for medical image segmentation
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T14:04:27.173350Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 673c6754-b33f-4120-9bfb-bef8ab1d3a63 · inbound
A BERT-Style Self-Supervised Learning CNN for Disease Identification from Retinal Images cites this paper.
A BERT-Style Self-Supervised Learning CNN for Disease Identification from Retinal Images LadderNet: Multi-path networks based on U-Net for medical image segmentation
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:28:30.749888Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 542a3723-5f4f-4dfb-918b-4792cb927e0b · inbound
Deep Wave Network for Modeling Multi-Scale Physical Dynamics cites this paper.
Deep Wave Network for Modeling Multi-Scale Physical Dynamics LadderNet: Multi-path networks based on U-Net for medical image segmentation
Reference 88
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T17:31:05.105501Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6bd7ac0f-5baf-4287-8f12-a2750443d048 · inbound
CurvSegFlow: Time-Conditioned Flow Matching for Robust Segmentation of Curvilinear Structures in Noisy Biomedical Images cites this paper.
CurvSegFlow: Time-Conditioned Flow Matching for Robust Segmentation of Curvilinear Structures in Noisy Biomedical Images LadderNet: Multi-path networks based on U-Net for medical image segmentation
Reference 67
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T06:19:37.374502Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 56f7e008-96ec-4a08-8bf8-77a520aeeb2d · inbound
Luminosity-Adaptive Contrast Enhancement Using CLAHE for Retinal Fundus Images with Quantitative Validation and Comparative Analysis cites this paper.
Luminosity-Adaptive Contrast Enhancement Using CLAHE for Retinal Fundus Images with Quantitative Validation and Comparative Analysis LadderNet: Multi-path networks based on U-Net for medical image segmentation
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T17:21:01.024074Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.