LogoXpertNet: a novel lightweight logo classification using deep learning.

Mumtaz MT, Awang MK, Saeed MU, Hussain S, Ben Noureddine D, Daadaa Y

Open source

DOI: 10.1038/s41598-026-45682-z
Published: 2026 Mar 26
Container: Scientific reports
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1038/s41598-026-45682-z,
  title = {LogoXpertNet: a novel lightweight logo classification using deep learning.},
  author = {Mumtaz MT and Awang MK and Saeed MU and Hussain S and Ben Noureddine D and Daadaa Y},
  year = {2026},
  journal = {Scientific reports},
  doi = {10.1038/s41598-026-45682-z},
  url = {https://doi.org/10.1038/s41598-026-45682-z}
}

RIS

TY  - JOUR
TI  - LogoXpertNet: a novel lightweight logo classification using deep learning.
AU  - Mumtaz MT
AU  - Awang MK
AU  - Saeed MU
AU  - Hussain S
AU  - Ben Noureddine D
AU  - Daadaa Y
PY  - 2026
JO  - Scientific reports
DO  - 10.1038/s41598-026-45682-z
UR  - https://doi.org/10.1038/s41598-026-45682-z
ER  -

APA

MT, M., MK, A., MU, S., S, H., D, B. N., & Y, D. (2026). LogoXpertNet: a novel lightweight logo classification using deep learning.. Scientific reports. https://doi.org/10.1038/s41598-026-45682-z

Source records

pubmed · retrieved 2026-09-26T01:03:23.221Z
europe-pmc · retrieved 2026-09-26T01:03:23.232Z
doaj · retrieved 2026-09-26T01:03:23.249Z