Hyperspectral dual-comb compressive ghost imaging with deep learning reconstruction.
- DOI
- 10.1038/s41377-026-02417-z
- Published
- 2026 Sep 16
- Container
- Light, science & applications
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- supportingOpen access status: Normalized open-access status: open.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1038/s41377-026-02417-z,
title = {Hyperspectral dual-comb compressive ghost imaging with deep learning reconstruction.},
author = {Suh MG and Dang D and Gao M and Jin Y and Shin DC and Gupta A and Park BJ and Uzundal C and Hu B and Kort-Kamp WJM and Lee HWH},
year = {2026},
journal = {Light, science \& applications},
doi = {10.1038/s41377-026-02417-z},
url = {https://doi.org/10.1038/s41377-026-02417-z}
}RIS
TY - JOUR TI - Hyperspectral dual-comb compressive ghost imaging with deep learning reconstruction. AU - Suh MG AU - Dang D AU - Gao M AU - Jin Y AU - Shin DC AU - Gupta A AU - Park BJ AU - Uzundal C AU - Hu B AU - Kort-Kamp WJM AU - Lee HWH PY - 2026 JO - Light, science & applications DO - 10.1038/s41377-026-02417-z UR - https://doi.org/10.1038/s41377-026-02417-z ER -
APA
MG, S., D, D., M, G., Y, J., DC, S., A, G., BJ, P., C, U., B, H., WJM, K., & HWH, L. (2026). Hyperspectral dual-comb compressive ghost imaging with deep learning reconstruction.. Light, science & applications. https://doi.org/10.1038/s41377-026-02417-z
Source records
- pubmed · retrieved 2026-09-25T23:05:28.842Z