A CNN-LSTM-att hybrid model for classification and evaluation of growth status under drought and heat stress in chinese fir (Cunninghamia lanceolata).
- DOI
- 10.1186/s13007-023-01044-8
- Published
- 2023 Jul 3
- Container
- Plant methods
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1186/s13007-023-01044-8,
title = {A CNN-LSTM-att hybrid model for classification and evaluation of growth status under drought and heat stress in chinese fir (Cunninghamia lanceolata).},
author = {Xing D and Wang Y and Sun P and Huang H and Lin E},
year = {2023},
journal = {Plant methods},
doi = {10.1186/s13007-023-01044-8},
url = {https://doi.org/10.1186/s13007-023-01044-8}
}RIS
TY - JOUR TI - A CNN-LSTM-att hybrid model for classification and evaluation of growth status under drought and heat stress in chinese fir (Cunninghamia lanceolata). AU - Xing D AU - Wang Y AU - Sun P AU - Huang H AU - Lin E PY - 2023 JO - Plant methods DO - 10.1186/s13007-023-01044-8 UR - https://doi.org/10.1186/s13007-023-01044-8 ER -
APA
D, X., Y, W., P, S., H, H., & E, L. (2023). A CNN-LSTM-att hybrid model for classification and evaluation of growth status under drought and heat stress in chinese fir (Cunninghamia lanceolata).. Plant methods. https://doi.org/10.1186/s13007-023-01044-8
Source records
- pubmed · retrieved 2026-09-26T18:51:58.080Z