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Paper Citation Record · LEDGER

CrosswalkNet: An Optimized Deep Learning Framework for Pedestrian Crosswalk Detection in Aerial Images with High-Performance Computing

As of 19 August 2026, this Paper Citation Record lists 3 of 3 outbound references and 1 inbound Pith citation observation for arXiv:2506.07885.

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

pith.paper-citation-record.v1
2506.07885 v1

Coverage vector

measured 3 of 3 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:27:03.796236Z

measured 4 of 4 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T17:54:27.453779Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

3 of 3 outbound references displayed

  • verified exact0
  • verified fuzzy2
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a8b0ac79-3bc2-49ca-a43c-c9230f827572 · outbound

This paper cites intersection,.

CrosswalkNet: An Optimized Deep Learning Framework for Pedestrian Crosswalk Detection in Aerial Images with High-Performance Computing intersection,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:27:03.968468Z

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=2026-08-07T05:27:03.787570Z digest=sha256:a7385bed060b3b8f5ec2bef31ea8902c6e75faa38d9929f964dd0d3e0a7ec632

Observation 7614552b-ea59-46ec-80d2-f133d6a7f329 · outbound

This paper cites slicing" was employed, in which the images were divided into smaller, overlapping segments or.

CrosswalkNet: An Optimized Deep Learning Framework for Pedestrian Crosswalk Detection in Aerial Images with High-Performance Computing slicing" was employed, in which the images were divided into smaller, overlapping segments or

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:27:03.958069Z

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=2026-08-07T05:27:03.792231Z digest=sha256:4abddcfa8c0bccefd9c921729e10d5e61e88cc93c20efd3a49de15df5a68b821

Observation 7cd85cab-2247-411f-a080-5979b226903b · outbound

This paper cites an unresolved cited work.

CrosswalkNet: An Optimized Deep Learning Framework for Pedestrian Crosswalk Detection in Aerial Images with High-Performance Computing Unresolved cited work

Reference 5

Resolution
metadata mismatch
raw_fallback, observed 2026-08-07T05:27:03.945129Z

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=2026-08-07T05:27:03.796236Z digest=sha256:d25afa4022303d31ec790e56a0206d6e5af59e8d1a0e92960856679d8f9377ee

Pith citing papers

Observation d94b5640-6d2a-4b0d-b24c-18ced799aa75 · inbound

TraversRL: Traversable Pedestrian Pathway Generation With Reinforcement Learning cites this paper.

TraversRL: Traversable Pedestrian Pathway Generation With Reinforcement Learning CrosswalkNet: An Optimized Deep Learning Framework for Pedestrian Crosswalk Detection in Aerial Images with High-Performance Computing

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-01T17:54:27.453779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:54:27.453779Z digest=sha256:2dbd9c6e67bb2b5ab4bd31107638d5f41673427725d774a9b7c0260cc2f332b8