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Paper Citation Record · LEDGER

ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1910.03151.

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

pith.paper-citation-record.v1
1910.03151 v4

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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:55:38.572727Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T09:11:00.395616Z

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 cc1d8b4b-7481-4c7f-a5c1-b0eb637bb87d · inbound

Achieving 3D Attention via Triplet Squeeze and Excitation Block cites this paper.

Achieving 3D Attention via Triplet Squeeze and Excitation Block ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-15T22:55:38.572727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:55:38.572727Z digest=sha256:69d782a22fbaa81ce8c45b89c9ad8ab878c71307b6262d8ae72a43e4875a089c

Observation 44787829-9ab3-4f63-8606-0014aafe7096 · inbound

OTProf: estimating high-resolution profiles of optical turbulence ($C_n^2$) from reanalysis using deep learning cites this paper.

OTProf: estimating high-resolution profiles of optical turbulence ($C_n^2$) from reanalysis using deep learning ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:11:00.402760Z

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.

source=pdf_text observed=2026-05-10T16:12:12.797697Z digest=sha256:f9df130e9b0f09745d33a47e5d7118ff4d7b4b028846e861dfd151b526f8c477