Lightweight audiovisual attention cross-perception network for video saliency prediction.
- DOI
- 10.1016/j.neunet.2026.109756
- Published
- 2027 Feb
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- unknown
Credibility signals
limited evidence Score 43/100 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.
- 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.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2026.109756,
title = {Lightweight audiovisual attention cross-perception network for video saliency prediction.},
author = {Bao L and Hu Z and Jin Y and Zhou X and Zhang G and Liu D},
year = {2027},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2026.109756},
url = {https://doi.org/10.1016/j.neunet.2026.109756}
}RIS
TY - JOUR TI - Lightweight audiovisual attention cross-perception network for video saliency prediction. AU - Bao L AU - Hu Z AU - Jin Y AU - Zhou X AU - Zhang G AU - Liu D PY - 2027 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2026.109756 UR - https://doi.org/10.1016/j.neunet.2026.109756 ER -
APA
L, B., Z, H., Y, J., X, Z., G, Z., & D, L. (2027). Lightweight audiovisual attention cross-perception network for video saliency prediction.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2026.109756
Source records
- pubmed · retrieved 2026-11-10T13:47:19.421Z