Tan, Z.; Yang, J.; Li, Q.; Su, F.; Yang, T.; Wang, W.; Aierxi, A.; Zhang, X.; Yang, W.; Kong, J.;
et al. PollenDetect: An Open-Source Pollen Viability Status Recognition System Based on Deep Learning Neural Networks. Int. J. Mol. Sci. 2022, 23, 13469.
https://doi.org/10.3390/ijms232113469
AMA Style
Tan Z, Yang J, Li Q, Su F, Yang T, Wang W, Aierxi A, Zhang X, Yang W, Kong J,
et al. PollenDetect: An Open-Source Pollen Viability Status Recognition System Based on Deep Learning Neural Networks. International Journal of Molecular Sciences. 2022; 23(21):13469.
https://doi.org/10.3390/ijms232113469
Chicago/Turabian Style
Tan, Zhihao, Jing Yang, Qingyuan Li, Fengxiang Su, Tianxu Yang, Weiran Wang, Alifu Aierxi, Xianlong Zhang, Wanneng Yang, Jie Kong,
and et al. 2022. "PollenDetect: An Open-Source Pollen Viability Status Recognition System Based on Deep Learning Neural Networks" International Journal of Molecular Sciences 23, no. 21: 13469.
https://doi.org/10.3390/ijms232113469
APA Style
Tan, Z., Yang, J., Li, Q., Su, F., Yang, T., Wang, W., Aierxi, A., Zhang, X., Yang, W., Kong, J., & Min, L.
(2022). PollenDetect: An Open-Source Pollen Viability Status Recognition System Based on Deep Learning Neural Networks. International Journal of Molecular Sciences, 23(21), 13469.
https://doi.org/10.3390/ijms232113469