Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Change Detection Between Optical Remote Sensing Imagery and Map Data via Segment Anything Model (SAM)
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2401.09019.
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 2026-08-16T05:46:06.316792Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T05:30:23.456663Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
0
pith, observed 2026-08-10T05:30:23.456663Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 2c3c48b8-b5d8-4948-8f32-652301c07a78 · inbound
A Survey of Sample-Efficient Deep Learning for Change Detection in Remote Sensing: Tasks, Strategies, and Challenges cites this paper.
A Survey of Sample-Efficient Deep Learning for Change Detection in Remote Sensing: Tasks, Strategies, and Challenges Change Detection Between Optical Remote Sensing Imagery and Map Data via Segment Anything Model (SAM)
Reference 173
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T10:59:37.847140Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 96524970-b028-4cfd-9b2b-3cb4cc5e62fb · inbound
SRMF: A Data Augmentation and Multimodal Fusion Approach for Long-Tail UHR Satellite Image Segmentation cites this paper.
SRMF: A Data Augmentation and Multimodal Fusion Approach for Long-Tail UHR Satellite Image Segmentation Change Detection Between Optical Remote Sensing Imagery and Map Data via Segment Anything Model (SAM)
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T05:46:06.316792Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5131dc4d-fbda-4e75-9f54-f12f75cd3473 · inbound
MergeSAM: Unsupervised change detection of remote sensing images based on the Segment Anything Model cites this paper.
MergeSAM: Unsupervised change detection of remote sensing images based on the Segment Anything Model Change Detection Between Optical Remote Sensing Imagery and Map Data via Segment Anything Model (SAM)
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T11:27:58.623875Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cc96f81a-ad0f-4b7f-ba5a-5f89b647e526 · inbound
Information transmission: Inferring change area from change moment in time series remote sensing images cites this paper.
Information transmission: Inferring change area from change moment in time series remote sensing images Change Detection Between Optical Remote Sensing Imagery and Map Data via Segment Anything Model (SAM)
Reference 105
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T11:11:13.082153Z
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.