Remote Sensing Image Scene Classification with SE-EfficientNetV2-S: An Empirical Study of Channel Attention and Semi-Supervised Pseudo-Labeling

Liting Liao, Haoyuan Yang, Jun Peng, Runqiu Jin

Open source

DOI: 10.3390/s26144617
Published: 2026-07-21
Container: Sensors
Publisher: MDPI AG
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. Source: Crossref; license: CC0 metadata
supportingDOI resolves: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
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. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.3390/s26144617,
  title = {Remote Sensing Image Scene Classification with SE-EfficientNetV2-S: An Empirical Study of Channel Attention and Semi-Supervised Pseudo-Labeling},
  author = {Liting Liao and Haoyuan Yang and Jun Peng and Runqiu Jin},
  year = {2026},
  journal = {Sensors},
  doi = {10.3390/s26144617},
  url = {https://doi.org/10.3390/s26144617}
}

RIS

TY  - JOUR
TI  - Remote Sensing Image Scene Classification with SE-EfficientNetV2-S: An Empirical Study of Channel Attention and Semi-Supervised Pseudo-Labeling
AU  - Liting Liao
AU  - Haoyuan Yang
AU  - Jun Peng
AU  - Runqiu Jin
PY  - 2026
JO  - Sensors
DO  - 10.3390/s26144617
UR  - https://doi.org/10.3390/s26144617
ER  -

APA

Liao, L., Yang, H., Peng, J., & Jin, R. (2026). Remote Sensing Image Scene Classification with SE-EfficientNetV2-S: An Empirical Study of Channel Attention and Semi-Supervised Pseudo-Labeling. Sensors. https://doi.org/10.3390/s26144617

Source records

crossref · retrieved 2026-09-25T08:27:42.265Z