Non-destructive geographical authentication of coffee beans: A hyperspectral-guided RGB imaging approach with optimized deep learning algorithms
- DOI
- 10.1016/j.saa.2026.128777
- Published
- 2027-01
- Container
- Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.saa.2026.128777,
title = {Non-destructive geographical authentication of coffee beans: A hyperspectral-guided RGB imaging approach with optimized deep learning algorithms},
author = {Siheng Lu and Yifei Du and Jing Zhao and Yue Yu and Yue Huang and Fuliang Cao and Zhanming Li},
year = {2027},
journal = {Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy},
doi = {10.1016/j.saa.2026.128777},
url = {https://doi.org/10.1016/j.saa.2026.128777}
}RIS
TY - JOUR TI - Non-destructive geographical authentication of coffee beans: A hyperspectral-guided RGB imaging approach with optimized deep learning algorithms AU - Siheng Lu AU - Yifei Du AU - Jing Zhao AU - Yue Yu AU - Yue Huang AU - Fuliang Cao AU - Zhanming Li PY - 2027 JO - Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy DO - 10.1016/j.saa.2026.128777 UR - https://doi.org/10.1016/j.saa.2026.128777 ER -
APA
Lu, S., Du, Y., Zhao, J., Yu, Y., Huang, Y., Cao, F., & Li, Z. (2027). Non-destructive geographical authentication of coffee beans: A hyperspectral-guided RGB imaging approach with optimized deep learning algorithms. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. https://doi.org/10.1016/j.saa.2026.128777
Source records
- crossref · retrieved 2026-09-25T08:49:17.758Z