The following publications are possibly variants of this publication:
- Combined Use of FCN and Harris Corner Detection for Counting Wheat Ears in Field ConditionsDaoyong Wang, Yuanyuan Fu, Guijun Yang, Xiaodong Yang, Dong Liang, Chengquan Zhou, Ning Zhang, Hongya Wu, Dongyan Zhang. access, 7:178930-178941, 2019. [doi]
- SSRNet: In-Field Counting Wheat Ears Using Multi-Stage Convolutional Neural NetworkDaoyong Wang, Dongyan Zhang, Guijun Yang, Bo Xu 0017, Yaowu Luo, Xiaodong Yang. tgrs, 60:1-11, 2022. [doi]
- Research on the Method of Counting Wheat Ears via Video Based on Improved YOLOv7 and DeepSortTianle Wu, Suyang Zhong, Hao Chen, Xia Geng. sensors, 23(10):4880, 2023. [doi]
- Wheat Ear Recognition Based on RetinaNet and Transfer LearningJingbo Li, Changchun Li, Shuaipeng Fei, Chunyan Ma, Weinan Chen, Fan Ding, Yilin Wang, Yacong Li, Jinjin Shi, Zhen Xiao. sensors, 21(14):4845, 2021. [doi]
- Lightweight convolutional neural network model for field wheat ear disease identificationWenxia Bao, Xinghua Yang, Dong Liang 0009, Gensheng Hu, Xianjun Yang. cea, 189:106367, 2021. [doi]