Efficient fine-tuning of large-scale vision-language models for visual marketing analysis: From brand logo detection to aesthetic preference prediction

Suxiang Qin, Songwen Wei

Open source

DOI: 10.1371/journal.pone.0354157
Published: 2026-08-07
Container: PLOS One
Publisher: Public Library of Science (PLoS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0354157,
  title = {Efficient fine-tuning of large-scale vision-language models for visual marketing analysis: From brand logo detection to aesthetic preference prediction},
  author = {Suxiang Qin and Songwen Wei},
  year = {2026},
  journal = {PLOS One},
  doi = {10.1371/journal.pone.0354157},
  url = {https://doi.org/10.1371/journal.pone.0354157}
}

RIS

TY  - JOUR
TI  - Efficient fine-tuning of large-scale vision-language models for visual marketing analysis: From brand logo detection to aesthetic preference prediction
AU  - Suxiang Qin
AU  - Songwen Wei
PY  - 2026
JO  - PLOS One
DO  - 10.1371/journal.pone.0354157
UR  - https://doi.org/10.1371/journal.pone.0354157
ER  -

APA

Qin, S., & Wei, S. (2026). Efficient fine-tuning of large-scale vision-language models for visual marketing analysis: From brand logo detection to aesthetic preference prediction. PLOS One. https://doi.org/10.1371/journal.pone.0354157

Source records

crossref · retrieved 2026-11-08T07:38:29.102Z