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Paper Citation Record · LEDGER

Quantum Machine Learning for Remote Sensing: Exploring potential and challenges

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2311.07626.

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

pith.paper-citation-record.v1
2311.07626 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T01:30:19.480943Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T06:15:57.303047Z

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 21b1e07a-385b-48c0-b11a-b49209eef7f9 · inbound

HQF-Net: A Hybrid Quantum-Classical Multi-Scale Fusion Network for Remote Sensing Image Segmentation cites this paper.

HQF-Net: A Hybrid Quantum-Classical Multi-Scale Fusion Network for Remote Sensing Image Segmentation Quantum Machine Learning for Remote Sensing: Exploring potential and challenges

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:15:57.305245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T17:44:10.366364Z digest=sha256:9565581d6ba1fbf93b99136845a209a2ac729480e8383ccc1a18f98d789f134a

Observation 36ffdbf4-b935-449a-b9e4-a0d58492672c · inbound

Hybrid Quantum CNN for Cross-Sensor Spaceborne Volcanic Thermal Activity Recognition Worldwide cites this paper.

Hybrid Quantum CNN for Cross-Sensor Spaceborne Volcanic Thermal Activity Recognition Worldwide Quantum Machine Learning for Remote Sensing: Exploring potential and challenges

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-04T01:28:23.555133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T01:28:23.555133Z digest=sha256:bab668f9d736d60112de157f0aeaa3ef22a0019ec2878d5c1a770269099e81cb

Observation e3196dc1-a574-4163-9036-62551767efde · inbound

Volcanic Clouds Detection through QCNN and Geostationary Satellite Multispectral Imagery cites this paper.

Volcanic Clouds Detection through QCNN and Geostationary Satellite Multispectral Imagery Quantum Machine Learning for Remote Sensing: Exploring potential and challenges

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-04T01:30:19.480943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T01:30:19.480943Z digest=sha256:54d066bec2b90b19990288c6a3c228d86b2f8807931f04b8278f7a1d75c0859f