Learning Compact Multispectral Signatures for Geographical-Origin Authentication of <i>Pinellia ternata</i> via Correlation-Guided Deep Modeling.
- DOI
- 10.3390/molecules31173138
- Published
- 2026-09-07
- Container
- Molecules
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/molecules31173138,
title = {Learning Compact Multispectral Signatures for Geographical-Origin Authentication of \<i\>Pinellia ternata\</i\> via Correlation-Guided Deep Modeling.},
author = {Fan Z and Jing S and Ma C and Wang S and Chen Z and Huang J and Zhang M.},
year = {2026},
journal = {Molecules},
doi = {10.3390/molecules31173138},
url = {https://doi.org/10.3390/molecules31173138}
}RIS
TY - JOUR TI - Learning Compact Multispectral Signatures for Geographical-Origin Authentication of <i>Pinellia ternata</i> via Correlation-Guided Deep Modeling. AU - Fan Z AU - Jing S AU - Ma C AU - Wang S AU - Chen Z AU - Huang J AU - Zhang M. PY - 2026 JO - Molecules DO - 10.3390/molecules31173138 UR - https://doi.org/10.3390/molecules31173138 ER -
APA
Z, F., S, J., C, M., S, W., Z, C., J, H., & M., Z. (2026). Learning Compact Multispectral Signatures for Geographical-Origin Authentication of <i>Pinellia ternata</i> via Correlation-Guided Deep Modeling.. Molecules. https://doi.org/10.3390/molecules31173138
Source records
- europe-pmc · retrieved 2026-09-25T02:34:37.327Z