A Self-Supervised Anomaly Detector of Fruits Based on Hyperspectral Imaging.

Liu Y, Zhou S, Wan Z, Qiu Z, Zhao L, Pang K, Li C, Yin Z.

Open source

DOI
10.3390/foods12142669
Published
2023-07-11
Container
Foods
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.3390/foods12142669,
  title = {A Self-Supervised Anomaly Detector of Fruits Based on Hyperspectral Imaging.},
  author = {Liu Y and  Zhou S and  Wan Z and  Qiu Z and  Zhao L and  Pang K and  Li C and  Yin Z.},
  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  - Liu Y
AU  -  Zhou S
AU  -  Wan Z
AU  -  Qiu Z
AU  -  Zhao L
AU  -  Pang K
AU  -  Li C
AU  -  Yin Z.
PY  - 2023
JO  - Foods
DO  - 10.3390/foods12142669
UR  - https://doi.org/10.3390/foods12142669
ER  -

APA

Y, L., S, Z., Z, W., Z, Q., L, Z., K, P., C, L., & Z., Y. (2023). A Self-Supervised Anomaly Detector of Fruits Based on Hyperspectral Imaging.. Foods. https://doi.org/10.3390/foods12142669

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