Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Analysis of Deep Learning-Based Colorization and Super-Resolution Techniques for Lidar Imagery
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.11532.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T04:06:30.670202Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T19:53:37.124809Z
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 04f58864-6940-4821-82df-0d71f97da6a1 · inbound
Enhancing Lidar Point Cloud Sampling via Colorization and Super-Resolution of Lidar Imagery cites this paper.
Enhancing Lidar Point Cloud Sampling via Colorization and Super-Resolution of Lidar Imagery Analysis of Deep Learning-Based Colorization and Super-Resolution Techniques for Lidar Imagery
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T04:06:30.670202Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 68208cf8-3f11-40c0-ad22-b26154006fec · inbound
SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds cites this paper.
SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Analysis of Deep Learning-Based Colorization and Super-Resolution Techniques for Lidar Imagery
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:14:35.608087Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 369e998c-001b-4717-b1b9-6ade020f1053 · inbound
Lidar Variability: A Novel Dataset and Comparative Study of Solid-State and Spinning Lidars cites this paper.
Lidar Variability: A Novel Dataset and Comparative Study of Solid-State and Spinning Lidars Analysis of Deep Learning-Based Colorization and Super-Resolution Techniques for Lidar Imagery
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T19:53:37.230647Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.