Nondestructive 3D phenotyping method of passion fruit based on X-ray micro-computed tomography and deep learning.
- DOI
- 10.3389/fpls.2022.1087904
- Published
- 2022
- Container
- Frontiers in plant science
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3389/fpls.2022.1087904,
title = {Nondestructive 3D phenotyping method of passion fruit based on X-ray micro-computed tomography and deep learning.},
author = {Lu Y and Wang R and Hu T and He Q and Chen ZS and Wang J and Liu L and Fang C and Luo J and Fu L and Yu L and Liu Q},
year = {2022},
journal = {Frontiers in plant science},
doi = {10.3389/fpls.2022.1087904},
url = {https://doi.org/10.3389/fpls.2022.1087904}
}RIS
TY - JOUR TI - Nondestructive 3D phenotyping method of passion fruit based on X-ray micro-computed tomography and deep learning. AU - Lu Y AU - Wang R AU - Hu T AU - He Q AU - Chen ZS AU - Wang J AU - Liu L AU - Fang C AU - Luo J AU - Fu L AU - Yu L AU - Liu Q PY - 2022 JO - Frontiers in plant science DO - 10.3389/fpls.2022.1087904 UR - https://doi.org/10.3389/fpls.2022.1087904 ER -
APA
Y, L., R, W., T, H., Q, H., ZS, C., J, W., L, L., C, F., J, L., L, F., L, Y., & Q, L. (2022). Nondestructive 3D phenotyping method of passion fruit based on X-ray micro-computed tomography and deep learning.. Frontiers in plant science. https://doi.org/10.3389/fpls.2022.1087904
Source records
- pubmed · retrieved 2026-09-26T04:41:43.552Z