Dehaze-attention: enhancing image dehazing with a multi-scale, attention-based deep learning framework
- DOI
- 10.1038/s41598-025-27959-x
- Published
- 2025-12-19
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- 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.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- 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.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1038/s41598-025-27959-x,
title = {Dehaze-attention: enhancing image dehazing with a multi-scale, attention-based deep learning framework},
author = {Hao Huang and G. T. S. Ho and M. W. Geda and Minghao Li and Yuk Ming Tang},
year = {2025},
journal = {Scientific Reports},
doi = {10.1038/s41598-025-27959-x},
url = {https://doi.org/10.1038/s41598-025-27959-x}
}RIS
TY - JOUR TI - Dehaze-attention: enhancing image dehazing with a multi-scale, attention-based deep learning framework AU - Hao Huang AU - G. T. S. Ho AU - M. W. Geda AU - Minghao Li AU - Yuk Ming Tang PY - 2025 JO - Scientific Reports DO - 10.1038/s41598-025-27959-x UR - https://doi.org/10.1038/s41598-025-27959-x ER -
APA
Huang, H., Ho, G. T. S., Geda, M. W., Li, M., & Tang, Y. M. (2025). Dehaze-attention: enhancing image dehazing with a multi-scale, attention-based deep learning framework. Scientific Reports. https://doi.org/10.1038/s41598-025-27959-x
Source records
- crossref · retrieved 2026-09-26T09:45:39.735Z