A Self-Supervised Anomaly Detector of Fruits Based on Hyperspectral Imaging
- DOI
- 10.3390/foods12142669
- Published
- 2023-07-11
- Container
- Foods
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/foods12142669,
title = {A Self-Supervised Anomaly Detector of Fruits Based on Hyperspectral Imaging},
author = {Yisen Liu and Songbin Zhou and Zhiyong Wan and Zefan Qiu and Lulu Zhao and Kunkun Pang and Chang Li and Zexuan Yin},
year = {2023},
journal = {Foods},
doi = {10.3390/foods12142669},
url = {https://doi.org/10.3390/foods12142669}
}RIS
TY - JOUR TI - A Self-Supervised Anomaly Detector of Fruits Based on Hyperspectral Imaging AU - Yisen Liu AU - Songbin Zhou AU - Zhiyong Wan AU - Zefan Qiu AU - Lulu Zhao AU - Kunkun Pang AU - Chang Li AU - Zexuan Yin PY - 2023 JO - Foods DO - 10.3390/foods12142669 UR - https://doi.org/10.3390/foods12142669 ER -
APA
Liu, Y., Zhou, S., Wan, Z., Qiu, Z., Zhao, L., Pang, K., Li, C., & Yin, Z. (2023). A Self-Supervised Anomaly Detector of Fruits Based on Hyperspectral Imaging. Foods. https://doi.org/10.3390/foods12142669
Source records
- crossref · retrieved 2026-11-03T14:48:27.188Z