Cite
StomataTracker: Revealing circadian rhythms of wheat stomata with in-situ video and deep learning.
MLA
Sun, Zhuangzhuang, et al. “StomataTracker: Revealing Circadian Rhythms of Wheat Stomata with in-Situ Video and Deep Learning.” Computers & Electronics in Agriculture, vol. 212, Sept. 2023, p. N.PAG. EBSCOhost, https://doi.org/10.1016/j.compag.2023.108120.
APA
Sun, Z., Wang, X., Song, Y., Li, Q., Song, J., Cai, J., Zhou, Q., Zhong, Y., Jin, S., & Jiang, D. (2023). StomataTracker: Revealing circadian rhythms of wheat stomata with in-situ video and deep learning. Computers & Electronics in Agriculture, 212, N.PAG. https://doi.org/10.1016/j.compag.2023.108120
Chicago
Sun, Zhuangzhuang, Xiao Wang, Yunlin Song, Qing Li, Jin Song, Jian Cai, Qin Zhou, Yingxin Zhong, Shichao Jin, and Dong Jiang. 2023. “StomataTracker: Revealing Circadian Rhythms of Wheat Stomata with in-Situ Video and Deep Learning.” Computers & Electronics in Agriculture 212 (September): N.PAG. doi:10.1016/j.compag.2023.108120.