Author:
Wang Shu-Mao,Yu Cui-Ping,Ma Jun-Hui,Ouyang Jia-Xue,Zhao Zhu-Meng,Xuan Yi-Min,Fan Dong-Mei,Yu Jin-Feng,Wang Xiao-Chang,Zheng Xin-Qiang
Reference69 articles.
1. Bhatt, P.V., Sarangi, S., Pappula, S., 2019. Detection of diseases and pests on images captured in uncontrolled conditions from tea plantations. : Auton. Air Ground Sens. Syst. Agric. Optim. Phenotyping IV, Md., USA 1–10. 10.1117/12.2518868..
2. Modeling the directional anisotropy of fine-scale TIR emissions over tree and crop canopies based on UAV measurements;Bian;Remote Sens Environ.,2021
3. bubbliiiing, 2022. YOLOv5-Pytorch, [WWW Document]. URL, https://github.com/bu bbliiiing/yolov5-pytorch.
4. Bioavailability of tea catechins and its improvement;Cai;Molecules,2018
5. Lightweight tea bud recognition network integrating Ghostnet and YOLOv5;Cao;Math. Biosci. Eng.,2022