Lightweight residual deep learning framework for urea and formalin adulteration detection in milk using hyperspectral imaging

Padmasri P, Sathya Bama B

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DOI: 10.1080/19440049.2026.2729045
Published: 2026-09-25
Container: Food Additives & Contaminants: Part A
Publisher: Informa UK Limited
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1080/19440049.2026.2729045,
  title = {Lightweight residual deep learning framework for urea and formalin adulteration detection in milk using hyperspectral imaging},
  author = {Padmasri P and Sathya Bama B},
  year = {2026},
  journal = {Food Additives \&amp; Contaminants: Part A},
  doi = {10.1080/19440049.2026.2729045},
  url = {https://doi.org/10.1080/19440049.2026.2729045}
}

RIS

TY  - JOUR
TI  - Lightweight residual deep learning framework for urea and formalin adulteration detection in milk using hyperspectral imaging
AU  - Padmasri P
AU  - Sathya Bama B
PY  - 2026
JO  - Food Additives &amp; Contaminants: Part A
DO  - 10.1080/19440049.2026.2729045
UR  - https://doi.org/10.1080/19440049.2026.2729045
ER  -

APA

P, P., & B, S. B. (2026). Lightweight residual deep learning framework for urea and formalin adulteration detection in milk using hyperspectral imaging. Food Additives & Contaminants: Part A. https://doi.org/10.1080/19440049.2026.2729045

Source records

crossref · retrieved 2026-09-26T07:00:26.493Z