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Paper Citation Record · LEDGER

TreeLearn: A deep learning method for segmenting individual trees from ground-based LiDAR forest point clouds

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2309.08471.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2309.08471 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:22:26.735447Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-19T06:47:07.108637Z

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 59a66870-b4c3-43ab-9c28-b646b54fdb25 · inbound

ForestFormer3D: A Unified Framework for End-to-End Segmentation of Forest LiDAR 3D Point Clouds cites this paper.

ForestFormer3D: A Unified Framework for End-to-End Segmentation of Forest LiDAR 3D Point Clouds TreeLearn: A deep learning method for segmenting individual trees from ground-based LiDAR forest point clouds

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-15T19:22:26.735447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:22:26.735447Z digest=sha256:b33295f4292f502c5f2121c3795b00def107abf37cde70b7464fcd2eb8f49f65

Observation 22830ba4-8025-4a4a-a35c-58b5f0aa4ebd · inbound

SelvaBox: A high-resolution dataset for tropical tree crown detection cites this paper.

SelvaBox: A high-resolution dataset for tropical tree crown detection TreeLearn: A deep learning method for segmenting individual trees from ground-based LiDAR forest point clouds

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-19T06:47:07.111219Z

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.

source=pdf_text observed=2026-05-19T06:46:30.488456Z digest=sha256:b588f43473dec76426d150138b632ae01930f3a8a49bbd486fa9da441f188a38