A multi-scale attention multi-task 1D-CNN for predicting rice chemical components at different milling degrees using hyperspectral imaging
- DOI
- 10.1016/j.foodchem.2026.151980
- Published
- 2026-12
- Container
- Food Chemistry
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.foodchem.2026.151980,
title = {A multi-scale attention multi-task 1D-CNN for predicting rice chemical components at different milling degrees using hyperspectral imaging},
author = {Ze Sun and Mengyuan Wang and Hao Li and Anqi Li and Yanlong Han and Haonan Gao and Tianyi Wang},
year = {2026},
journal = {Food Chemistry},
doi = {10.1016/j.foodchem.2026.151980},
url = {https://doi.org/10.1016/j.foodchem.2026.151980}
}RIS
TY - JOUR TI - A multi-scale attention multi-task 1D-CNN for predicting rice chemical components at different milling degrees using hyperspectral imaging AU - Ze Sun AU - Mengyuan Wang AU - Hao Li AU - Anqi Li AU - Yanlong Han AU - Haonan Gao AU - Tianyi Wang PY - 2026 JO - Food Chemistry DO - 10.1016/j.foodchem.2026.151980 UR - https://doi.org/10.1016/j.foodchem.2026.151980 ER -
APA
Sun, Z., Wang, M., Li, H., Li, A., Han, Y., Gao, H., & Wang, T. (2026). A multi-scale attention multi-task 1D-CNN for predicting rice chemical components at different milling degrees using hyperspectral imaging. Food Chemistry. https://doi.org/10.1016/j.foodchem.2026.151980
Source records
- crossref · retrieved 2026-11-08T00:11:16.042Z